Search

Radiation-induced acoustics (RIA) shows promise in advancing radiological imaging and radiotherapy dosimetry methods. However, RIA signals often require extensive averaging to achieve reasonable signal-to-noise ratios, which increases patient radiation exposure and limits real-time applications. Therefore, this paper proposes a discrete wavelet transform (DWT) based filtering approach to denoise the RIA signals and avoid extensive averaging. The algorithm was benchmarked against low-pass filters and tested on various types of RIA sources, including low-energy X-rays, high-energy X-rays, and protons. The proposed method significantly reduced the required averages (1000 times less averaging for low-energy X-ray RIA, 32 times less averaging for high-energy X-ray RIA, and 4 times less averaging for proton RIA) and demonstrated robustness in filtering signals from different sources of radiation. The coif5 wavelet in conjunction with the sqtwolog threshold selection algorithm yielded the best results. The proposed DWT filtering method enables high-quality, automated, and robust filtering of RIA signals, with a performance similar to low-pass filtering, aiding in the clinical translation of radiation-based acoustic imaging for radiology and radiation oncology.

Abstract Broadband couplers consist usually of multiple coupled lines that are each a quarter wave‐length long. Herein, in contrast to conventional methods, a short length of a microstrip line is coupled to a coaxial line. The length of the coupled microstrip line is small compared to the wavelength at the lowest operating frequency. The coupling is weak and the microstrip line is λ/8 at the highest operating frequency. The proposed structure resembles a pair of coupled lines with a linear coupling response. The coupling exhibits a slope of 6 dB/octave over multi‐octave bandwidth. The microstrip line is connected to a lumped element compensating network at the coupled port. The compensating network is a low‐pass circuit with a slope of −6 dB/octave. The power handling of the coupler is high due to the coaxial line and the weakly coupled microstrip line. Electromagnetic simulations and analytical formulations are presented. The broadband coupler handles nearly 1 kW of input power. Due to the weak coupling of the microstrip‐coaxial coupler, the lumped element circuit needs to handle

Abstract The linear power amplifier (LPA) suffers from low power supply utilization in the DC power supply mode, leading to reduced output efficiency. This paper constructs an efficient power supply mode based on closed‐loop dynamic power supply system (CLDPSs). The CLDPSs can generate a pair of bipolar dynamic power supplies based on a predetermined signal to provide power to LPA, which can maintain a small voltage drop between the power supply and the output of LPA, thereby improving the power supply utilization of LPA. In addition, the study also focuses on the conflicting relationship between the output ripple and the dynamic performance of the CLDPSs, for which a new parametric design of the LC filter circuit is proposed, aiming to achieve a balance between these two aspects. Finally, a voice coil motor driving platform is constructed for experimental testing. The results demonstrate that the output ripple and dynamic performance of the CLDPSs can be balanced. In comparison to the DC power supply mode, the CLDPSs power supply mode can enhance the efficiency of LPA by 2 times while the driving accuracy of voice coil motor is basically unchanged.

Abstract The high penetration of renewable energy sources (RES) results in a low‐inertia, weak power grid. To mitigate this and restore system inertia, it has been widely proposed to operate the inverters of RES units to mimic synchronous generators; this technology is known as a virtual synchronous generator (VSG). In weak grids there is, however, strong coupling between active power (P) and reactive power (Q), and any VSG technique therefore requires PQ decoupling in order to operate effectively. This article proposes a new PQ decoupling technique based on the transformation of the PQ power circle of a VSG connected to a weak grid: first, the power circle is translated from its designed position to that of a conventional synchronous generator (SG) connected to a strong grid, achieving partial PQ decoupling. Then, to achieve full PQ decoupling, the authors propose further to modulate the radius of the translated PQ power circle; this is achieved using a series resistance‐capacitance–inductance (RCL) circuit which is virtually implemented in the VSG controller. The efficacy of the proposed scheme is validated using a modified synchronverter connected to the weak grid in representative loading scenarios. It is demonstrated that the technique achieves a decoupled PQ control for the synchronverter connected in a weak grid. Moreover, the modified synchronverter is capable of supporting frequency and voltage regulation in the grid without inducing large transient grid currents during mild frequency and voltage variations.

The linear power amplifier (LPA) suffers from low power supply utilization in the DC power supply mode, leading to reduced output efficiency. This paper constructs an efficient power supply mode based on closed‐loop dynamic power supply system (CLDPSs). The CLDPSs can generate a pair of bipolar dynamic power supplies based on a predetermined signal to provide power to LPA, which can maintain a small voltage drop between the power supply and the output of LPA, thereby improving the power supply utilization of LPA. In addition, the study also focuses on the conflicting relationship between the output ripple and the dynamic performance of the CLDPSs, for which a new parametric design of the LC filter circuit is proposed, aiming to achieve a balance between these two aspects. Finally, a voice coil motor driving platform is constructed for experimental testing. The results demonstrate that the output ripple and dynamic performance of the CLDPSs can be balanced. In comparison to the DC power supply mode, the CLDPSs power supply mode can enhance the efficiency of LPA by 2 times while the driving accuracy of voice coil motor is basically unchanged. [ABSTRACT FROM AUTHOR]

Broadband couplers consist usually of multiple coupled lines that are each a quarter wave‐length long. Herein, in contrast to conventional methods, a short length of a microstrip line is coupled to a coaxial line. The length of the coupled microstrip line is small compared to the wavelength at the lowest operating frequency. The coupling is weak and the microstrip line is λ/8 at the highest operating frequency. The proposed structure resembles a pair of coupled lines with a linear coupling response. The coupling exhibits a slope of 6 dB/octave over multi‐octave bandwidth. The microstrip line is connected to a lumped element compensating network at the coupled port. The compensating network is a low‐pass circuit with a slope of −6 dB/octave. The power handling of the coupler is high due to the coaxial line and the weakly coupled microstrip line. Electromagnetic simulations and analytical formulations are presented. The broadband coupler handles nearly 1 kW of input power. Due to the weak coupling of the microstrip‐coaxial coupler, the lumped element circuit needs to handle <1.5 W. A high‐power coupler has been fabricated for the frequency range of 30 to 500 MHz. It exhibits a coupling response of 56 ± 0.4 dB. [ABSTRACT FROM AUTHOR]

The high penetration of renewable energy sources (RES) results in a low‐inertia, weak power grid. To mitigate this and restore system inertia, it has been widely proposed to operate the inverters of RES units to mimic synchronous generators; this technology is known as a virtual synchronous generator (VSG). In weak grids there is, however, strong coupling between active power (P$P$) and reactive power (Q$Q$), and any VSG technique therefore requires PQ$PQ$ decoupling in order to operate effectively. This article proposes a new PQ$PQ$ decoupling technique based on the transformation of the PQ$PQ$ power circle of a VSG connected to a weak grid: first, the power circle is translated from its designed position to that of a conventional synchronous generator (SG) connected to a strong grid, achieving partialPQ$PQ$ decoupling. Then, to achieve full PQ$PQ$ decoupling, the authors propose further to modulate the radius of the translated PQ$PQ$ power circle; this is achieved using a series resistance‐capacitance–inductance (RCL$RCL$) circuit which is virtually implemented in the VSG controller. The efficacy of the proposed scheme is validated using a modified synchronverter connected to the weak grid in representative loading scenarios. It is demonstrated that the technique achieves a decoupled PQ$PQ$ control for the synchronverter connected in a weak grid. Moreover, the modified synchronverter is capable of supporting frequency and voltage regulation in the grid without inducing large transient grid currents during mild frequency and voltage variations. [ABSTRACT FROM AUTHOR]

The problem of super-resolution is concerned with the reconstruction of temporally/spatially localized events (or spikes) from samples of their convolution with a low-pass filter. Distinct from prior works which exploit sparsity in appropriate domains in order to solve the resulting ill-posed problem, this paper explores the role of binary priors in super-resolution, where the spike (or source) amplitudes are assumed to be binary-valued. Our study is inspired by the problem of neural spike deconvolution, but also applies to other applications such as symbol detection in hybrid millimeter wave communication systems. This paper makes several theoretical and algorithmic contributions to enable binary super-resolution with very few measurements. Our results show that binary constraints offer much stronger identifiability guarantees than sparsity, allowing us to operate in "extreme compression" regimes, where the number of measurements can be significantly smaller than the sparsity level of the spikes. To ensure exact recovery in this "extreme compression" regime, it becomes necessary to design algorithms that exactly enforce binary constraints without relaxation. In order to overcome the ensuing computational challenges, we consider a first order auto-regressive filter (which appears in neural spike deconvolution), and exploit its special structure. This results in a novel formulation of the super-resolution binary spike recovery in terms of binary search in one dimension. We perform numerical experiments that validate our theory and also show the benefits of binary constraints in neural spike deconvolution from real calcium imaging datasets.

In this Letter, we introduce and experimentally verify a very simple tunable-phase oscillator structure based on cascaded standard filter sections. In particular, a standard inverting second-order low-pass filter is cascaded with a first-order bi-linear filter in a closed loop resulting in a third-order structure that can be made marginally stable. The phase difference between the outputs of the two filter sections is a design parameter that is tunable independent of the oscillation frequency or start-up gain. [ABSTRACT FROM AUTHOR]

Accurately estimating whole-body angular momentum (WBAM) during daily activities may benefit from choosing a locally-defined reference frame aligned with anatomical axes, particularly during activities involving body turns. Local reference frames, potentially defined by pelvis heading angles, horizontal center of mass velocity (vCoM), or average angular velocity (${A}\omega $), can be utilized. To minimize the impact of inherent mediolateral oscillations of these frames, such as those caused by pelvis or vCoM rotation in the transverse plane, a low-pass filter is recommended. This study investigates how differences among global, local reference frames pre- and post-filtering affect WBAM component distribution across anatomical axes during straight-line walking and various turning tasks, which is lacking in the literature. Results highlighted significant effects of reference frame choice on WBAM distribution in the anteroposterior (AP) and mediolateral (ML) axes in all tasks. Specifically, expressing WBAM in the vCoM-oriented local reference frame yielded significantly lower (or higher) WBAM in the AP (or ML) axes compared to pelvis-oriented and ${A}\omega $ -oriented frames. However, these significant differences disappeared after employing a low-pass filter to local reference frames. Therefore, employing low-pass filtered local reference frames is crucial to enhance their applicability in both straight-line and turning tasks, ensuring more precise WBAM estimates. In applications that require expressing anatomical axes-dependent biomechanical parameters in a local reference frame, pelvis- and vCoM-oriented frames are more practical compared to the A $\omega $ -oriented frame, as they can be determined by a reduced optical marker set or inertial sensors in future applications when the whole-body kinematics is not available. [ABSTRACT FROM AUTHOR]

Hydrogeodesy can benefit greatly from the use of global positioning system (GPS) displacements to analyze local changes in the hydrosphere, which the commonly used Gravity Recovery and Climate Experiment (GRACE) mission is unable to provide due to coarse spatial resolution. Hydrosphere changes recorded by GPS are unfortunately hidden among the other signals to which the system is also sensitive, so the sensitivity of GPS to changes in the hydrosphere on temporal scales from pluri-annual to decadal is questionable. We focus on hydrosphere signatures present on these long-term temporal scales as observed by GPS through the vertical displacement time series (DTS) of 122 permanent stations over Europe and compare them to the DTS derived from GRACE for GPS locations. Our methodology is based on the weighted Savitzky–Golay (S-G) filter, an underestimated filter in the field of geodetic time-series analysis. We show that the correspondence between GPS and GRACE on long-term temporal scales is generally strong, but decreases for coastal regions and regions where the coarse gridding of GRACE does not capture local hydrosphere effects. Furthermore, the negative correlation with El Niño Southern Oscillations (ENSO) is confirmed for Europe. [ABSTRACT FROM AUTHOR]

Review of both classical and rarely used methods for synthesis of digital and analogue frequency-selective filters is presented. For continuous filters, different transfer functions are considered. For digital filters, a description of various optimization methods is given. Parametric families of sampling mappings are discussed. Methods for filter synthesis using atomic functions are described. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Millimetre‐wave radar offers high ranging accuracy and can capture subtle vibration information of the human heart. This study proposes a heartbeat prediction method based on the transformer model using millimetre‐wave radar. Firstly, the millimetre‐wave radar was used to collect the heartbeat data and conduct normalisation processing. Secondly, a position coding was introduced to assign sine or cosine variables to input data and extract their relative position relationship. Subsequently, the transformer encoder was adopted to allocate attention to input data through the multi‐head attention mechanism, using a mask layer before the decoding layer to prevent the leakage of future information. Finally, we employ the fully connected layer was employed in the linear decoder for regression and output the predicted results. Our experimental results demonstrate that the proposed transformer model achieves nearly 30% higher prediction accuracy than traditional long short‐term memory models while improving both the prediction accuracy and convergence rate. The proposed method has great potential in predicting the heartbeat state of elderly and sick patients.

Abstract The conventional lowpass prototype filter with the finite transmission zeros close‐to‐band edge often yields negative circuit elements that lead to a practical difficulty of physical realizations. This paper presents an alternative topology of the lowpass prototype filter named three element resonator lowpass filter, which is composed of series inductances and shunt three element resonators. For one‐section three element resonator lowpass filter, the closed‐form solutions of the non‐negative circuit elements are deduced based on its characteristic function recovered from a prescribed transmission zero. For multi‐section one, the associated numerical synthesis procedure using gradient‐based optimization is presented. In physical realization, a much more practical configuration of three element resonator is proven by the equivalent circuit transformation. A synthesis example of lowpass prototype filter with 12 pairs of transmission zeros illustrates the effectiveness of the numerical synthesis method. Also, a design example of five‐section three element resonator lowpass filter, which has a passband up to 1775 MHz, is implemented by the distributed elements based on its prototype circuit of the numerical synthesis. The measured results of the fabricated lowpass filter experimentally validate the prototype filter.

Depth maps generally suffer from large erroneous areas even in public RGB-Depth datasets. Existing learning-based depth recovery methods are limited by insufficient high-quality datasets and optimization-based methods generally depend on local contexts not to effectively correct large erroneous areas. This paper develops an RGB-guided depth map recovery method based on the fully connected conditional random field (dense CRF) model to jointly utilize local and global contexts of depth maps and RGB images. A high-quality depth map is inferred by maximizing its probability conditioned upon a low-quality depth map and a reference RGB image based on the dense CRF model. The optimization function is composed of redesigned unary and pairwise components, which constraint local structure and global structure of depth map, respectively, with the guidance of RGB image. In addition, the texture-copy artifacts problem is handled by two-stage dense CRF models in a coarse-to-fine way. A coarse depth map is first recovered by embedding RGB image in a dense CRF model in unit of $3\times 3$ blocks. It is refined afterward by embedding RGB image in another model in unit of individual pixels and restricting the model mainly work in discontinued regions. Extensive experiments on six datasets verify that the proposed method considerably outperforms a dozen of baseline methods in correcting erroneous areas and diminishing texture-copy artifacts of depth maps. [ABSTRACT FROM AUTHOR]

Understanding how motor units (MUs) contribute to skeletal mechanical force is crucial for unraveling the underlying mechanism of human movement. Alterations in MU firing, contractile and force-generating properties emerge in response to physical training, aging or injury. However, how changes in MU firing and twitch properties dictate skeletal muscle force generation in healthy and impaired individuals remains an open question. In this work, we present a MU-specific approach to identify firing and twitch properties of MU samples and employ them to decode musculoskeletal function in vivo. First, MU firing events were decomposed offline from high-density electromyography (HD-EMG) of six lower leg muscles involved in ankle plantar-dorsi flexion. We characterized their twitch responses based on the statistical distributions of their firing properties and employed them to compute MU-specific activation dynamics. Subsequently, we decoded ankle joint moments by linking our framework to a subject-specific musculoskeletal model. We validated our approach at different ankle positions and levels of activation and compared it with traditional EMG-driven models. Our proposed MU-specific formulation achieves higher generalization across conditions than the EMG-driven models, with significantly lower coefficients of variation in torque predictions. Furthermore, our approach shows distinct neural strategies across a large repertoire of contractile conditions in different muscles. Our proposed approach may open new avenues for characterizing the relationship between MU firing and twitch properties and their influence on force capacity. This can facilitate the development of targeted rehabilitation strategies tailored to individuals with specific neuromuscular conditions. [ABSTRACT FROM AUTHOR]

Transfemoral prosthesis users (TFPUs) typically have a high risk of balance loss and falling. Whole-body angular momentum (${\overrightarrow {H}}_{{\text {WB}}}{)}$ is a common measure for assessing dynamic balance during human walking. However, little is known about how unilateral TFPUs maintain this dynamic balance through segment-to-segment cancellation strategies. Better understanding of the underlying mechanisms of dynamic balance control in TFPUs is required to improve gait safety. Thus, this study aimed to evaluate dynamic balance in unilateral TFPUs during walking at a self-selected constant speed. Fourteen unilateral TFPUs and fourteen matched controls performed level-ground walking at a comfortable speed on a straight, 10-m-long walkway. In the sagittal plane, the TFPUs had a greater and smaller range of $\overrightarrow {H}_{{\text {WB}}}$ compared to controls during intact and prosthetic steps, respectively. Further, the TFPUs generated greater average positive and negative $\overrightarrow {H}_{{\text {WB}}}$ than did the controls during intact and prosthetic steps, respectively, which may necessitate larger step-to-step postural changes in the forward and backward rotation about the body center of mass (COM). In the transverse plane, no significant difference was observed in the range of $\overrightarrow {H}_{{\text {WB}}}$ between groups. However, the TFPUs displayed smaller negative average $\overrightarrow {H}_{{\text {WB}}}$ in the transverse plane than did the controls. In the frontal plane, the TFPUs and controls demonstrated similar range of $\overrightarrow {H}_{{\text {WB}}}$ and step-to-step whole-body dynamic balance owing to the employment of different segment-to-segment cancellation strategies. Our findings should be interpreted and generalized with caution for the demographic features in our participants. [ABSTRACT FROM AUTHOR]

Complementary Linear Filter (CLF) is a common techinque employed for estimating the ground projection of body Centre of Mass starting from ground reaction forces. This method fuses centre of pressure position and double integration of horizontal forces, selecting best cut-off frequencies for low-pass and high-pass filters. Classical Kalman filter is a substantially equivalent approach, as both methods rely on an overall quantification of error/noise and don’t analyze its origin and time-dependence. In order to overcome such limitations, a Time-Varying Kalman Filter (TVKF) is proposed in this paper: the effect of unknown variables is directly taken into account by employing a statistical description which is obtained from experimental data. To this end, in this paper we have employed a dataset of 8 walking healthy subjects: beside supplying gait cycles at different speeds, it deals with subjects in age of development and provides a wide range of body sizes, allowing therefore to assess the observers’ behaviour under different conditions. The comparison carried out between CLF and TVKF appears to highlight several advantages of the latter method in terms of better average performance and smaller variability. Results presented in this paper suggest that a strategy which incorporates a statistical description of unknown variables and a time-varying structure can yield a more reliable observer. The demonstrated methodology sets a tool that can undergo a broader investigation to be carried out including more subjects and different walking styles. [ABSTRACT FROM AUTHOR]

Motor brain-computer interface (BCI) can intend to restore or compensate for central nervous system functionality. In the motor-BCI, motor execution (ME), which relies on patients’ residual or intact movement functions, is a more intuitive and natural paradigm. Based on the ME paradigm, we can decode voluntary hand movement intentions from electroencephalography (EEG) signals. Numerous studies have investigated EEG-based unimanual movement decoding. Moreover, some studies have explored bimanual movement decoding since bimanual coordination is important in daily-life assistance and bilateral neurorehabilitation therapy. However, the multi-class classification of the unimanual and bimanual movements shows weak performance. To address this problem, in this work, we propose a neurophysiological signatures-driven deep learning model utilizing the movement-related cortical potentials (MRCPs) and event-related synchronization/ desynchronization (ERS/D) oscillations for the first time, inspired by the finding that brain signals encode motor-related information with both evoked potentials and oscillation components in ME. The proposed model consists of a feature representation module, an attention-based channel-weighting module, and a shallow convolutional neural network module. Results show that our proposed model has superior performance to the baseline methods. Six-class classification accuracies of unimanual and bimanual movements achieved 80.3%. Besides, each feature module of our model contributes to the performance. This work is the first to fuse the MRCPs and ERS/D oscillations of ME in deep learning to enhance the multi-class unimanual and bimanual movements’ decoding performance. This work can facilitate the neural decoding of unimanual and bimanual movements for neurorehabilitation and assistance. [ABSTRACT FROM AUTHOR]

The existing remote sensing (RS) image dehazing methods based on deep learning have sought help from the convolutional frameworks. Nevertheless, the inherent limitations of convolution, i.e., local receptive fields and independent input elements, curtail the network from learning the long-range dependencies and nonuniform distributions. To this end, we design an effective RS image dehazing Transformer architecture, denoted as RSDformer. First, given the irregular shapes and nonuniform distributions of haze in RS images, capturing both local and non-local features is crucial for RS image dehazing models. Hence, we propose a detail-compensated transposed attention (DCTA) to extract the global and local dependencies (LDs) across channels. Second, to enhance the ability to learn degraded features and better guide the restoration process, we develop a dual-frequency adaptive block (DFAB) with dynamic filters. Finally, a dynamic gated fusion block (DGFB) is designed to achieve fuse and exchange features across different scales effectively. In this way, the model exhibits robust capabilities to capture dependencies from both global and local areas, resulting in improving image content recovery. Extensive experiments prove that the proposed method obtains more appealing performances against other competitive methods. [ABSTRACT FROM AUTHOR]

In this letter, we address the problem of combating the effect of the nonlinearities of the transmit–receive chain in solid-state radars, which are typically generated by the power amplifier (PA) in transmission. This issue is of particular importance in meteorological radar applications, as they require to transmit pulse featuring very low autocorrelation sidelobes, which are significantly raised due to nonlinearities. In this work, we describe an adaptive predistortion design method based on an iterative approach in the spectral domain. The proposed method has been validated by means of hardware using a customized software radio and driving an amplifier into saturation. Two different ideal, highly performing pulse compression waveforms, expressly designed for weather radar applications, were sent to its input. The experimental results demonstrate the benefits of the proposed approach to design the digital predistortion module. [ABSTRACT FROM AUTHOR]

Millimetre‐wave radar offers high ranging accuracy and can capture subtle vibration information of the human heart. This study proposes a heartbeat prediction method based on the transformer model using millimetre‐wave radar. Firstly, the millimetre‐wave radar was used to collect the heartbeat data and conduct normalisation processing. Secondly, a position coding was introduced to assign sine or cosine variables to input data and extract their relative position relationship. Subsequently, the transformer encoder was adopted to allocate attention to input data through the multi‐head attention mechanism, using a mask layer before the decoding layer to prevent the leakage of future information. Finally, we employ the fully connected layer was employed in the linear decoder for regression and output the predicted results. Our experimental results demonstrate that the proposed transformer model achieves nearly 30% higher prediction accuracy than traditional long short‐term memory models while improving both the prediction accuracy and convergence rate. The proposed method has great potential in predicting the heartbeat state of elderly and sick patients. [ABSTRACT FROM AUTHOR]

The conventional lowpass prototype filter with the finite transmission zeros close‐to‐band edge often yields negative circuit elements that lead to a practical difficulty of physical realizations. This paper presents an alternative topology of the lowpass prototype filter named three element resonator lowpass filter, which is composed of series inductances and shunt three element resonators. For one‐section three element resonator lowpass filter, the closed‐form solutions of the non‐negative circuit elements are deduced based on its characteristic function recovered from a prescribed transmission zero. For multi‐section one, the associated numerical synthesis procedure using gradient‐based optimization is presented. In physical realization, a much more practical configuration of three element resonator is proven by the equivalent circuit transformation. A synthesis example of lowpass prototype filter with 12 pairs of transmission zeros illustrates the effectiveness of the numerical synthesis method. Also, a design example of five‐section three element resonator lowpass filter, which has a passband up to 1775 MHz, is implemented by the distributed elements based on its prototype circuit of the numerical synthesis. The measured results of the fabricated lowpass filter experimentally validate the prototype filter. [ABSTRACT FROM AUTHOR]

Abstract Maximally flat digital differentiators (MFDDs) are very attractive for differentiation of narrowband signals. The design of infinite impulse response (IIR) MFDDs, however, is very challenging due to the non‐convexity of the flatness constraints of the IIR digital differentiator (DD). This study derives a set of linear conditions that are equivalent to the non‐convex flatness constraints and then utilises these conditions to design low‐pass and band‐pass IIR MFDDs with low and nearly constant group delay. In addition, a generalized‐positive‐realness‐based stability constraint is incorporated in the design to ensure the robust stability of the DD. A design algorithm is presented to maximise the total flatness degree subject to the flatness conditions and the stability constraint, resulting in maximally flat stable DDs (MFSDDs). Design examples and comparisons with existing DDs demonstrate that the designed IIR MFSDDs have better magnitude and group‐delay responses and lower implementation complexity.

This article presents a novel design procedure for fourth order and fourth-order resonance (4thRes) output filters, for given buck converter specifications, making components selection a straightforward process. An accurate filter analysis is provided to predict the filter component currents and voltages in both frequency and time domains. Application of the analysis in a design study of a 20 MHz, 5.4 W buck converter shows that the 4thRes filter has the potential to reduce the output passive components for a wide duty cycle range. As compared with a second-order filter at VIN = 6.6 V to VOUT = 1.8 V, total inductance, inductor energy, capacitance, and capacitor energy are 58%, 35%, 45%, and 31% lower, respectively. Air-core printed circuit board (PCB) integrated solenoid inductors are considered for implementation and testing within a prototype converter to show the impact of these filters on the converter performance. The 4thRes filter achieved 3.7% and 3.6% higher full-load efficiency than the second- and fourth-order filters, respectively, and a better load transient performance. [ABSTRACT FROM AUTHOR]

As theincrease of wind power penetration, the fluctuations of wind power results in serious power system frequency turbulences. This article proposes a low-pass virtual filter (VF) for wind energy conversion systems (WECSs) to smoothen output power. First, a linearized model is established for a WECS. Then, a low-pass VF is derived for the active power control loop in WECS to modulate the kinetic energy stored in rotating mass for output smoothing. The principle is to modify the traditional wind power controller to emulate a physical energy storage system controlled as a low-pass filter to smooth the wind power output. The proposed low-pass VF does not need the physical deployment of energy storage system but still can filter the high-frequency fluctuations in the output wind power. Furthermore, in order to ensure operation stability of the wind turbine (WT), a stability-constrained coefficient is determined according to the proposed stability criteria to ensure the stability of WTs. Simulation and experiment results verify the effectiveness of the proposed VF in WECS for output wind power fluctuation reduction and the stability-constrained coefficient for stability ensuring. [ABSTRACT FROM AUTHOR]

High-frequency resonance (HFR) in the modular multilevel converter (MMC) has been reported in recent years frequently, yet, existing focuses on HFR are limited to the specific control strategy or grid condition, from which the conclusion may be not applicable if the control or grid changes. In this article, a unified MMC high-frequency impedance model (UHFIM) is proposed to fill this gap. By changing the gain of the model, UHFIM can reflect the high-frequency characteristics of the MMC under different control strategies in a unified form, which provides a theoretical basis for the general HFR suppression method. Analysis based on UHFIM reveals the worst cases of the HFR risk and the constraint of low-pass filter (LPF) order on the convergence of MMC high-frequency damping. In order to suppress HFR, this article proposes a joint design method for LPF and passive damper, which can completely remove the HFR risk from the entire high-frequency range without sacrificing too much dynamic performance of MMC, and it works no matter how the grid impedance varies. Besides, in the case that the damper cannot be installed, an alternative HFR suppression method based on delay time adjustment is also developed. Finally, the proposed unified model and the HFR suppression methods have been verified by simulation and experimental results. [ABSTRACT FROM AUTHOR]

Power grids are evolving toward a highly distributed architecture with power-electronics circuits interfacing a majority of generation, storage, and loads. To ensure stability as synchronous machines are retired, grid-forming (GFM) inverters will be needed across the board. In this article, we investigate whether systems built with interconnected single-phase droop-controlled GFM inverters are capable of self organizing into balanced three-phase systems. We model, analyze, and build a system comprised of three delta-connected droop-controlled single-phase inverters connected across loads. After deriving a model of the angle dynamics for this system, we show that its stable equilibria coincide with balanced conditions, where each phase is offset by $1/3$ of an ac cycle. Furthermore, we observe that the desirable equilibrium with balanced phase offsets is robust against voltage and load imbalances. This demonstrates the feasibility of assembling three-phase systems using fleets of decentralized single-phase GFM inverters. The analytical developments are substantiated experimentally on a system of three delta-connected single-phase inverters. Spontaneous emergence of phase balancing from startup with nonidentical initial conditions are validated in the experimental setup. Empirical observations further illustrate robust operation during unbalanced conditions. [ABSTRACT FROM AUTHOR]

An analog baseband (ABB) spectrum sensing circuit is proposed for fast spectrum sensing. Contrast to the conventional RF scanner where it takes a relatively long period to detect channel and interference condition by sequentially controlling the center frequency of the filter, the proposed ABB circuit can scan it at a time using different bandwidths of low-pass filters with an almost equal out-of-band attenuation slope to sense the powers and frequencies of channel and interference. The ABB circuit is composed of two chains of five cascaded real and complex low-pass filters. The cut-off frequencies of five cascaded low-pass filters are set to be 10, 8, 6, 4 and 2 MHz respectively, regarding the channel bandwidth of 2 MHz. The orders of the five filters are optimized to be $4^{\mathrm{ th}}$ , $4^{\mathrm{ th}}$ , $3^{\mathrm{ rd}}$ , $2^{\mathrm{ nd}}$ , and $2^{\mathrm{ nd}}$ order respectively to make the rejected out-of-band power same for each filter for accurate detection. The filter core is designed on the basis of a flipped voltage follower and a super source follower for a low power dissipation and a high linearity, and the low power technique for implementing high-order filter is newly proposed in the design of filter chain. The measured frequency response at each output of the filter chain was almost the same to the simulation result. The measurement results show a noise figure (NF) of 19.2 dB, 22.1 dB, 24.8 dB, 25.1 dB, and 27 dB for each filters, and an in-band input-referred third-order intercept point (IIP3) of 9.2 dBm, 7.2 dBm, and 15.7 dBm at the output of $1^{\mathrm{ st}}$ , $3^{\mathrm{ rd}}$ , and last stages. The total power consumption of the filter chain is 10.4 mW from a 1.2 V supply voltage. [ABSTRACT FROM AUTHOR]

Due to the negative impedance potential of constant power loads (CPLs), the stability of power electronic converters-based electrical distribution networks is prone to instability. This brief proposes a robust control technique based on deep reinforcement learning to stabilize a DC microgrid (MG) with parallel boost converters when feeding CPLs. For this purpose, a model-free sliding mode controller (MFSMC) has been applied to the DC MG. The MFSMC controller does not need any identification of converters in the DC MG system while ensuring the efficiency and the stability of the control synthesis. The key control coefficients are designed by Proximal Policy Optimization (PPO) Reinforcement Learning (RL). The PPO is made from two deep neural networks (NNs) (actor NN and critic NN) which are trained to adjust the coefficients of the MFSMC controller. The MFSMC controller designed by the PPO with actor-critic architecture is applied to the DC MG system feeding CPL in an OPAL-RT setup to verify the efficiency of the proposed controller through Hardware-in-the-Loop (HiL) simulations. [ABSTRACT FROM AUTHOR]

Hybrid energy storage systems (HESS), i.e., the combination of two different energy storage technologies, are widely discussed as a promising solution for energy storage problems. A common control scheme to allocate the power between these storages and the subject of this study is filter-based control, where a filter splits the input signal into a low-frequency and high-frequency part. It provides robust results and easy implementation, although more advanced strategies may perform better. Many publications use this controller for specific problems, but a structured analysis of this controller type that quantifies the advantages and disadvantages, traits, and setbacks is missing. This work fills this gap and structures, summarizes, and provides mathematical background and guidelines on filter-based control of hybrid energy storage systems. Numerical simulations are performed to quantify the impact of design variables, parameters, or the input signal by using a linear storage model with efficiency and self-discharge rate and a low-pass filter controller with constant energy feedback as a representative subtype of this control scheme. The present work proves the high cycle-reduction capabilities of filter-controlled HESS at the cost of overdimensioning compared to more advanced control strategies. It demonstrates that using a high-efficiency, high-power storage with a low self-discharge rate and high-energy storage leads to smaller overall dimensioning and losses than a single storage system. The study identifies the feedback factor of the controller as the most impacting design variable.

The growing penetration of converter-interfaced distributed renewable energy sources (CI-DRES) has posed several challenges into the electric power systems, e.g., the instability caused by the intermittent nature of the primary sources, power quality issues, etc. Several algorithms have been proposed to mitigate the CI-DRES power fluctuations and reduce high active power ramp-rates (RRs) at the point of common coupling (PCC) with the grid using energy storage systems (ESS). However, these algorithms present some drawbacks. In this article, a new ramp-rate limitation (RRL) control method is proposed to address existing gaps in the technical literature. This algorithm is performed considering the connection of a supercapacitor (SC) at the dc-link of a DRES converter. The relationship between the SC voltage and the degree to which the RRL is achieved is established, aiming to reduce the SC voltage fluctuations and increase the SC life time. The RRL control is validated in a real experimental testbed and compared to state-of-the-art approaches. This control is also modeled in Matlab/Simulink in order to perform techno-economic investigations on the influence that several parameters (SC size, SC charging/discharging cycles, cost, etc.) have on the achieved RRL at the DRES PCC. [ABSTRACT FROM AUTHOR]

This article reveals the power and frequency oscillation mechanism of the islanded cascaded-type virtual synchronous generators (VSGs), and proposes a decentralized mutual damping suppression method. In the proposed scheme, the mutual damping term is constructed via the decentralized manner with transmission line current. It contributes to increasing damping and accelerating the frequency convergence of cascaded-type VSGs in the dynamic process. As a result, the power and frequency oscillations are restrained, and the system dynamic performance is improved. Further, the system stability based on the Lyapunov energy function method is proved. Finally, the effectiveness of the proposed decentralized mutual damping control is verified by simulations and experimental results. [ABSTRACT FROM AUTHOR]

The multiple second-order generalized integrator (MSOGI), which is composed of parallel second-order generalized integrators (SOGI), is widely used in grid synchronization and signal extraction, and it usually suffers from dc offset issue. In continuous domain, low-pass filter (LPF) can be added to SOGI to eliminate the dc offset in its quadrature channel. However, in digital implementation, directly discretized LPF-based methods may not be able to eliminate dc offset and ac discretization error simultaneously, where the steady-state error will also be introduced by the conventional frequency-locked loop (FLL). In this article, a modified impulse invariant method is adopted to discretize SOGIs, which presents zero ac errors and good dynamics, but shows dc offset in both output channels. Then, an LPF is introduced to eliminate the dc offset of the discrete SOGI, forming a discrete SOGI-LPF. And, a discrete MSOGI-LPF (DMSOGI-LPF) is formed by paralleling multiple DSOGI-LPFs, which can extract different frequency components. Furthermore, a discrete FLL is proposed to estimate the frequency of the input signal, which suppresses the influence of the dc offset and achieves good dynamics. Finally, the stability analysis of the proposed method based on discrete linear-time periodic (LTP) model is provided. The effectiveness of the proposed method and its discrete LTP model are validated through experimental results. [ABSTRACT FROM AUTHOR]

For permanent magnet synchronous linear motor (PMSLM), the traditional controller tuning method needs to identify the thrust coefficient and the mover mass separately. In order to simplify the parameter identification required for controller tuning of PMSLM, a strategy identifying the parameter named gain is proposed in this article. The gain is a parameter that combines the mover mass and thrust coefficient of PMSLM. The convergence time of the strategy is analyzed as well as the influence of the detent force on the identification error is investigated. After that, a controller tuning method based on the frequency domain is proposed and the geometric constraint relationship between the controller parameters is revealed. Eventually, combining the methods mentioned above, the experiment is carried out on a PMSLM prototype. The effectiveness of the proposed strategies is proved. [ABSTRACT FROM AUTHOR]

This work presents a third-order high-pass sigma-delta modulator (HPSDM) for biomedical signal acquisition. The operational amplifier (op-amp) sharing and noise-coupling techniques are adopted to reduce the required quantity of op-amps and add a noise-shaping order, which can achieve low power consumption and high resolution. A novel switched-capacitor architecture is proposed to suppress the increasing in-band noise and alleviate the circuit sensitivity to capacitor mismatch in the high-pass integrator. The proposed HPSDM was fabricated in a 0.18-μm standard CMOS process. Measurement results reveal that the proposed HPSDM has a signal-to-noise and distortion ratio (SNDR) of 75.26/74 dB in 200 Hz bandwidth and consumes 1.52/0.8 μW under 1.2/1 V supply voltage, which can achieve a peak Schreier Figure-of-Merit of 156.45/157.98 dB and a peak Walden FoM of 0.802/0.488 pJ/conv. [ABSTRACT FROM AUTHOR]

This letter proposes a simple and inexpensive control of distributed energy resources aimed at improving the power system dynamic performance. The rationale behind the proposed control relies on a recent interpretation of the frequency in the differential geometry framework. A comparison with well-established controls in terms of eigensensitivity and time-domain performance is carried out to show the effectiveness of the proposed control. [ABSTRACT FROM AUTHOR]

Designing a perfect filter (i.e., flat passband, sharp transition band, and highly suppressed stopband) is always the goal of digital signal processing practitioners. This goal is reachable if we make no consideration of implementation complexity. In other words, the challenge of designing a high-performance filter is to leverage the distortion tradeoff in the passband, transition band, and stopband. In this article, we introduce a trick for designing a composite filter by cascading the base filter with a notch filter for sharpening its transition band. The stopband of the base filter is then further shaped by complementary comb filters (CCFs), which are simple in complexity. Performing a delicate calculation of all these component filters, the passband of the composite filter is flat, and a near-perfect filter is obtained with reasonable complexity. [ABSTRACT FROM AUTHOR]

Generally speaking, a phase-locked loop (PLL) is a feedback circuit/algorithm that constantly adjusts its output to match in phase and frequency with a reference signal. In power/energy applications, the basis for developing the vast majority of available PLLs is the synchronous reference frame (SRF)-PLL, which is known to have a limited ability in filtering grid disturbances, particularly harmonics, interharmonics, and grid-voltage imbalance. Therefore, a common trend in designing more advanced PLLs is including additional filters within SRF-PLL control loops or before its input. Currently, the literature is full of contradictory remarks about the advantages/disadvantages of these filtering solutions, which are often collectively referred to as in-loop filters and prefilters. This article aims to take a deeper look at these filtering solutions and contribute to dispelling misconceptions about them. [ABSTRACT FROM AUTHOR]

An improved class AB version of the super source follower is used to implement a compact and power-efficient second order analog low-pass filter. The proposed circuit achieves a 41% power reduction as well as an improvement in linearity and pass band gain with respect to its class A counterpart. Measurement results of a test chip prototype fabricated in a 180 nm CMOS technology show a power consumption ranging from 50.3 $\mu \text{W}$ to 85.27 $\mu \text{W}$ for cutoff frequencies from 600 kHz to 890 kHz, with a supply voltage of ±0.75 V. A third order intermodulation distortion of −35.34 dB (for an input signal of 0.4 mVpp and 350 kHz) and a THD of −69.7 dB (for an input signal of 0.4 mVpp and 100 kHz) are measured, which results in an improvement with respect to the conventional class A version of 13.98 dB and 43.6 dB, respectively. The silicon area is 0.0592 mm2 (using external capacitors). [ABSTRACT FROM AUTHOR]

Due to short frames of short-term burst signals, the performance of conventional non-data-aided feedforward timing estimators is unsatisfactory. This letter investigates an estimator based on multiple cyclic correlations addressing this issue. The cyclic correlations at high-valued timing lags provide the timing information for estimating timing offset. Motivated by it, we combine the timing information at various timing lags, utilizing the second-order statistical characteristics of the limited sample data for accurate estimation. Considering the estimation range of roll-off factors and computational complexity, an asymptotically unbiased estimation using four correlations is deduced. Simulation results show that the proposed estimator outperforms other estimators. [ABSTRACT FROM AUTHOR]

Abstract Compressed sensing‐based radio frequency signal acquisition systems call for higher reconstruction speed and low dynamic power. In this study, a novel low power fast orthogonal matching pursuit (LPF‐OMP) algorithm is proposed for faster reconstruction of sparse signals from their compressively sensed samples and the reconstruction circuit consumes very low dynamic power. The searching time to find the best column is reduced by reducing the number of columns to be searched in successive iterations. A novel architecture of the proposed LPF‐OMP algorithm is also presented here. The proposed architecture is implemented on field programmable gate array for demonstrating the performance enhancement. Computation of pseudoinverse in OMP is avoided to save time and storage requirement to store the pseudoinverse matrix. The proposed design incorporates a novel strategy to stop the algorithm without consuming any extra circuitry. A case study is carried out to reconstruct the RADAR test pulses. The design is implemented for K = 256, N = 1024 using XILINX Virtex6 device and supports maximum of K/4 iterations. The proposed design is faster, hardware efficient and consumes very less dynamic power than the previous implementations of OMP. In addition, the proposed implementation proves to be efficient in reconstructing low sparse signals.

Abstract Penalized least squares (PLS) is a popular data smoothing technique. However, existing PLS smoothing algorithms behave as low‐pass filters (LPF), and, hence, they may introduce distortions to bandpass signals. These algorithms also have difficulties associated with the selection of the smoothing parameter and the order of the difference matrix they utilize. A new PLS smoothing algorithm is developed to overcome these limitations. In the proposed algorithm, two difference matrices and two regularisation parameters are utilized. As a result, the proposed algorithm can act as either an LPF or a bandpass filter. The particular shape of the filter is determined by the values of the regularisation parameters and the orders of the two difference matrices. The spectral characteristics of the smooth signal are utilized to derive closed‐form expressions for the optimum values of these four parameters. The derived algorithm is further developed to handle the case of having missing and/or outlier samples in the measured data. The proposed algorithms are completely data driven, and they do not require any special optimisation tools. In addition, the proposed algorithms are also shown to produce significantly improved results compared to some existing smoothing techniques.

In this article, an incremental quantities distance protection using Park's transformation is proposed to increase the operation speed of distance protection. Based on the instantaneous voltage in abc frame approximate linear distribution along the AC transmission lines, this article proves that instantaneous voltage in dq frame still satisfies the approximate linear distribution along the AC transmission line. Then, the d-axis voltage components of fault point and setting point are used to determine the internal and external faults. In order to ensure that the presented distance protection can be applied to all fault types, a virtual three-phase system construction method is also presented. The fault point voltage construction method and low-pass filter design method are also discussed. Finally, a typical AC transmission system is developed in PSCAD/EMTDC to verify the performance of the proposed distance protection under different fault conditions. Simulation results indicate that the proposed incremental quantities distance protection has fast operation speed under internal metallic fault conditions and high security under external fault conditions. [ABSTRACT FROM AUTHOR]

Seismic data interpolation and denoising play vital roles in obtaining complete and clean data in seismic data processing. Seismic data usually miss along various spatial axes and always mix with random noise. To obtain complete and clean seismic data, reconstruction technology can interpolate missing data and attenuate random noise. A nonsubsampled contourlet transform (NSCT) is an effective transform to obtain multiscale and multidirection sparse domain data for compression sensing interpolation and denoising. However, conventional iterative shrinkage/thresholding (IT) cannot handle ill-posed and ill-conditioned equations for solving linear inverse problem. We present a two-step iterative log thresholding (TwILT) method to overcome ill-posed and ill-conditioned problems and improve the convergence rate and solution accuracy, which can interpolate and denoise seismic data simultaneously in the NSCT framework. First, we use the NSCT to convert the seismic missing data with random noise to sparse domain. Then, we apply the TwILT algorithm to interpolate and denoise data in sparse domain. The result of each iteration is based on the results of the previous two iterations, which can accelerate convergence rate. In addition, log thresholding can further improve convergence rate and solution accuracy. Finally, we use inverse NSCT to obtain the interpolated and denoised seismic data. The new method can reconstruct the irregularly missing data and attenuate random noise to obtain complete and clean seismic data with high accuracy, which is crucial for seismic imaging and inversion. We demonstrate the applicability and effectiveness of this simultaneous interpolation and denoising technique with successful applications to both synthetic and field data examples. [ABSTRACT FROM AUTHOR]

A new design of a self-packaged all-printed circuit board (PCB) wideband filter based on the cascade connection of high-pass filter (HPF) and low-pass filter (LPF) is presented. The novel low- and high-pass quasi-lumped filter structure differs from the known ones by the existence of cross coupling between elements producing transmission zeroes (TZs) at the desired frequency. It is shown that high-order structures make it possible to design a wideband filter having the number of TZs in the low-frequency stopband equal to the order of the applied HPF and the number of TZs in the high-frequency stopband equal to half the order of the LPF. An implementation of two-layer metallization of the capacitor plates made it possible to manufacture all three types of filters using the common technology of multilayer PCBs with a good coincidence of the characteristics of the model and the fabricated filters. The filter fabricated using materials with a rather low quality factor (F4BM/RO4450B/RO4003C) has demonstrated a good performance: the central frequency is 0.99 GHz, the 1-dB fractional bandwidth is 152%, the minimum in-band loss is 0.3 dB, the selectivity ($\Delta f_{\mathrm {30~dB}}/\Delta f_{\mathrm {3~dB}}$) is 1.21, and the 40-dB stopband width is $6.16f_{0}$. [ABSTRACT FROM AUTHOR]

The introduction of new technology in the wireless communication industry increases the number of frequency bands in the communication environment. Therefore, a communication system capable of functioning over several frequency bands, known as a multiband communication system, is required. In addition, multiband communication systems support technology upgrades by smoothly bridging the migration from the existing technology to a newer technology. A multiband communication system can be developed with the help of two approaches. The first approach is a multiband communication system that contains multiple microwave circuits, with each circuit optimized for a single band; for example, a dual-band communication system has two low-pass filters and two power amplifiers. But this approach increases not only the size but also the cost of the system. In the second approach, rather than using a separate power amplifier and filter for each frequency band, a single power amplifier, filter, and other components are used that can support more than one frequency band. These circuits are known as multiband microwave circuits. Multiband circuits not only minimize size but also reduce the cost of designing the multiband communication system. [ABSTRACT FROM AUTHOR]

The electroencephalogram (EEG), for measuring the electrophysiological activity of the brain, has been widely applied in automatic detection of epilepsy seizures. Various EEG-based seizure detection algorithms have already yielded high sensitivity, but training those algorithms requires a large amount of labelled data. Data labelling is often done with a lot of human efforts, which is very time-consuming. In this study, we propose a hybrid system integrating an unsupervised learning (UL) module and a supervised learning (SL) module, where the UL module can significantly reduce the workload of data labelling. For preliminary seizure screening, UL synthesizes amplitude-integrated EEG (aEEG) extraction, isolation forest-based anomaly detection, adaptive segmentation, and silhouette coefficient-based anomaly detection evaluation. The UL module serves to quickly locate the determinate subjects (seizure segments and seizure-free segments) and the indeterminate subjects (potential seizure candidates). Afterwards, more robust seizure detection for the indeterminate subjects is performed by the SL using an EasyEnsemble algorithm. EasyEnsemble, as a class-imbalance learning method, can potentially decrease the generalization error of the seizure-free segments. The proposed method can significantly reduce the workload of data labelling while guaranteeing satisfactory performance. The proposed seizure detection system is evaluated using the Children’s Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) scalp EEG dataset, and it achieves a mean accuracy of 92.62%, a mean sensitivity of 95.55%, and a mean specificity of 92.57%. To the best of our knowledge, this is the first epilepsy seizure detection study employing the integration of both the UL and the SL modules, achieving a competitive performance superior or similar to that of the state-of-the-art methods. [ABSTRACT FROM AUTHOR]