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In this paper, a broadband multi‐carrier linear frequency modulation (LFM) signal reception method with subcarrier frequency offset deramp processing is proposed and investigated. The proposed frequency offset deramp processing is implemented by mixing the multi‐carrier LFM radar echo with a multi‐carrier LFM reference that has a different subcarrier frequency interval. With this design, the sampling rate of the radar receiver is remarkably reduced and crosstalk‐free separation of different subcarrier signals is easily conducted in the frequency domain. To fuse the multiple subcarriers and fill the frequency gaps, a sparse reconstruction method is employed to obtain the broadband response, which is essential for achieving high range resolution detection. The effectiveness of the proposed method is validated through an experiment in which the reception of an 8‐carrier LFM signal is conducted and a total bandwidth of 6 GHz after multi‐carrier fusion is demonstrated. An inverse synthetic aperture radar imaging experiment is also conducted with the results verifying the good potential of the proposed method in practical applications. [ABSTRACT FROM AUTHOR]

The data used during training in any given application space are directly tied to the performance of the system once deployed. While there are many other factors that are attributed to producing high-performance models based on the Neural Scaling Law within Machine Learning, there is no doubt that the data used to train a system provide the foundation from which to build. One of the underlying heuristics used within the Machine Learning space is that having more data leads to better models, but there is no easy answer to the question, "How much data is needed to achieve the desired level of performance?" This work examines a modulation classification problem in the Radio Frequency domain space, attempting to answer the question of how many training data are required to achieve a desired level of performance, but the procedure readily applies to classification problems across modalities. The ultimate goal is to determine an approach that requires the lowest amount of data collection to better inform a more thorough collection effort to achieve the desired performance metric. By focusing on forecasting the performance of the model rather than the loss value, this approach allows for a greater intuitive understanding of data volume requirements. While this approach will require an initial dataset, the goal is to allow for the initial data collection to be orders of magnitude smaller than what is required for delivering a system that achieves the desired performance. An additional benefit of the techniques presented here is that the quality of different datasets can be numerically evaluated and tied together with the quantity of data, and ultimately, the performance of the architecture in the problem domain. [ABSTRACT FROM AUTHOR]

To address the high-cost issue of twin single sideband quadrature phase shift keying (Twin-SSB-QPSK) signals in optical transmission, a optical fiber communication system was proposed, in which a single photodetector (PD) was employed at the receiver to directly detect the Twin-SSB-QPSK signals. At the receiver end, optical bandpass filter (OBPF) was not required to separate the two optical single sideband signals of the Twin-SSB-QPSK signal. Instead, the heterodyne effect of direct detection was utilized, allowing a single PD to directly detect the coherent superposition of the twin two optical single sideband QPSK signals, resulting in a single 16-ary quadrature amplitude modulation (16QAM) signal. Simulations demonstrated that two 56 Gbit/s QPSK signals were combined into a single 112 Gbit/s 16QAM signal and then compared with the traditional single 16QAM signal transmission scheme. The simulation results indicate that the proposed scheme does not introduce additional power penalties while reducing the system device requirements and deployment costs.

We propose a novel reception scheme for twin single-sideband (twin-SSB) signals using just a single photodetector (PD), significantly reducing the system complexity and cost. To detect a twin-SSB with power-unbalanced quadrature-phase shift keying (QPSK) sidebands upon detection via a single PD at the receiver side, two QPSKs carried in two sidebands are coherently superposed and detected in a 16-ary quadrature amplitude modulation (16-QAM) format. This technique notably diminishes the linearity and effective number of bits required for the transmitter components in high-speed optical transmission systems. Moreover, a hierarchical blind-phase search (HBPS) algorithm is proposed to compensate for the imperfect phase rotation of QPSK signals during transmission. To demonstrate the effectiveness of our proposed method, we successfully conducted simulations of 112 Gb/s 16-QAM signal transmission over a 10 km standard single-mode fiber (SSMF), achieving bit error ratios (BERs) of 7.84 × 10 − 4 , well below the 7% hard-decision forward error correction (HD-FEC) threshold of 3.8 × 10 − 3 . In addition, the synthetic transmission scheme proposed in this paper is compared with the traditional 16-QAM signal transmission scheme, and the results show that the proposed scheme does not introduce a performance cost with the same received optical power (ROP) and transmission distance. [ABSTRACT FROM AUTHOR]

Over the last years there has been plenty of research activity about modulation techniques with the aim of optimizing power converters performance. Traditional methods such as Pulse Width Modulation and Selective Harmonic Elimination/Mitigation are widely used but have limitations in harmonic performance and dynamic response. This paper aims at presenting a completely new approach in the synthesis process of control signals referred to as Pulse Position Modulation, which can generate the best possible control signal by adding up not-centered pulses in each control period. In particular, the proposed technique can optimize the positions of all the pulses making up the overall control signal thus allowing better harmonic performance compared to Pulse Width Modulation techniques featuring fixed position of the pulses. Moreover, the proposed technique allows for largely better dynamic performance in comparison to techniques such as Selective Harmonic Elimination/Mitigation that can similarly optimize the harmonic quality by modifying the position of the pulses. The paper includes a thorough mathematical analysis of the control signal synthesis technique, essential for correctly identifying the optimal pulse positions. A complete campaign of experimental tests proves the remarkable enhancement of this innovative approach in harmonic quality and dynamic performance compared to the above-mentioned techniques.

Abstract Upscaling of the time‐varying volume data is significant, since it can be used in in situ visualization to help scientists fast analyse complex simulations relevant to time‐varying volume data. A novel deep learning method called Pix2Pix spatial super‐resolution (Pix2PixSSR), which can be used to generate spatial super‐resolution of the time‐varying volume data is proposed here. It consists of two main components: One is a variant UNet‐like generator that takes the low resolution volume sequence as input and generates the high resolution counterparts; one is a PatchGAN discriminator that takes both low and high resolution volume sequences as input and predicts their realness. To validate its advantages, we qualitatively and quantitatively compare it with the state‐of‐the‐art upscaling techniques. More specifically, two experiments are performed. The first experiment uses the same variable of a time‐varying volume dataset for training and inference, while the second experiment uses different variables for training and inference. The experimental results show that for most cases, the Pix2PixSSR can generate the most similar super‐resolution to the ground truth, compared to the state‐of‐the‐art techniques.

Ground reaction force and moment (GRF&M) measurements are vital for biomechanical analysis and significantly impact the clinical domain for early abnormality detection for different neurodegenerative diseases. Force platforms have become the de facto standard for measuring GRF&M signals in recent years. Although the signal quality achieved from these devices is unparalleled, they are expensive and require laboratory setup, making them unsuitable for many clinical applications. For these reasons, predicting GRF&M from cheaper and more feasible alternatives has become a topic of interest. Several works have been done on predicting GRF&M from kinematic data captured from the subject's body with the help of motion capture cameras. The problem with these solutions is that they rely on markers placed on the whole body to capture the movements, which can be very infeasible in many practical scenarios. This paper proposes a novel deep learning-based approach to predict 3D GRF&M from only 5 markers placed on the shoe. The proposed network "Attention Guided MultiResUNet" can predict the force and moment signals accurately and reliably compared to the techniques relying on full-body markers. The proposed deep learning model is tested on two publicly available datasets containing data from 66 healthy subjects to validate the approach. The framework has achieved an average correlation coefficient of 0.96 for 3D ground reaction force prediction and 0.86 for 3D ground reaction momentum prediction in cross-dataset validation. The framework can provide a cheaper and more feasible alternative for predicting GRF&M in many practical applications. [ABSTRACT FROM AUTHOR]

Upscaling of the time‐varying volume data is significant, since it can be used in in situ visualization to help scientists fast analyse complex simulations relevant to time‐varying volume data. A novel deep learning method called Pix2Pix spatial super‐resolution (Pix2PixSSR), which can be used to generate spatial super‐resolution of the time‐varying volume data is proposed here. It consists of two main components: One is a variant UNet‐like generator that takes the low resolution volume sequence as input and generates the high resolution counterparts; one is a PatchGAN discriminator that takes both low and high resolution volume sequences as input and predicts their realness. To validate its advantages, we qualitatively and quantitatively compare it with the state‐of‐the‐art upscaling techniques. More specifically, two experiments are performed. The first experiment uses the same variable of a time‐varying volume dataset for training and inference, while the second experiment uses different variables for training and inference. The experimental results show that for most cases, the Pix2PixSSR can generate the most similar super‐resolution to the ground truth, compared to the state‐of‐the‐art techniques. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control 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.)

The detection of arrhythmias from wearable devices is still an open challenge, while the availability of screening tools for the large population would allow reduced complications and costs. We propose a model-based approach to the detection and classification of premature contractions into atrial and ventricular. The extracted signal morphology and the deviations from the expected stationarity are used to detect and classify premature contractions. Our approach is self-contained, patient-specific and robust to mis-segmentation. Both model fit, and detection and classification accuracy of the proposed methods are evaluated on two real cases and a simulated dataset, and show promising results. [ABSTRACT FROM AUTHOR]

We propose a novel reception scheme for twin single-sideband (twin-SSB) signals using just a single photodetector (PD), significantly reducing the system complexity and cost. To detect a twin-SSB with power-unbalanced quadrature-phase shift keying (QPSK) sidebands upon detection via a single PD at the receiver side, two QPSKs carried in two sidebands are coherently superposed and detected in a 16-ary quadrature amplitude modulation (16-QAM) format. This technique notably diminishes the linearity and effective number of bits required for the transmitter components in high-speed optical transmission systems. Moreover, a hierarchical blind-phase search (HBPS) algorithm is proposed to compensate for the imperfect phase rotation of QPSK signals during transmission. To demonstrate the effectiveness of our proposed method, we successfully conducted simulations of 112 Gb/s 16-QAM signal transmission over a 10 km standard single-mode fiber (SSMF), achieving bit error ratios (BERs) of 7.84×10−4, well below the 7% hard-decision forward error correction (HD-FEC) threshold of 3.8×10−3. In addition, the synthetic transmission scheme proposed in this paper is compared with the traditional 16-QAM signal transmission scheme, and the results show that the proposed scheme does not introduce a performance cost with the same received optical power (ROP) and transmission distance.

A system, the synthesis convolver, is described that can process the output of an analysis filter bank and: • Reconstruct the analysis filter bank input signal, • Implement continuous convolution on the reconstructed signal, and • Resample the reconstructed signal to different sample rates. The synthesis convolver combines the capabilities of a synthesis filter bank and a continuous convolver. The synthesis convolver is based on earlier work but improves upon it, adding convolution and resampling. As well as reconstructing filterbank data, convolution allows dechirping of pulsar signals and resampling allows synthesized data to conform to the VLBI VDIF standard. The spectral overlap-add approach described, compared to earlier work, reduces errors and is more robust to channel gain errors. The system uses windows with smoothed or apodized edges, with the classical Tukey window being used previously. Here the Tukey window is generalized leading to a class of apodized windows. This class of windows is explored and one is found that is close to optimal in all conditions and can reduce errors by up to 40 dB compared to an equivalent Tukey window. Achievable aliasing errors are lower than those of a standard polyphase synthesis filter bank. The synthesis convolver provides a high quality and versatile replacement for polyphase synthesis filter banks. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering 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.)

In this article, a complementary metal–oxide–semiconductor (CMOS) frequency and duty cycle controller (FDCC) is presented for on-chip signal synthesis. The circuit consists of a few logic gates and a voltage-controlled oscillator, and is functionally similar to a programmable divide-by-N frequency divider. It is designed for driving integrated sensor and actuator systems. Compared with other frequency dividers with the same control flexibility, the proposed circuit features a compact topology and allows the control over the output signal duty cycle. For the proof-of-concept, a prototype 1 × 4 array of identical FDCCs has been fabricated on a 0. 35 μ m Austria Mikro Systeme (AMS) CMOS process. Each FDCC occupies an active area of 0. 0051 mm 2 , which is area-efficient. The array has been validated to generate 4 synchronized 4 MHz ∼ 64 MHz outputs with a duty cycle tuning range of 3. 125 % ∼ 96. 875 %. Although driven by a 5- V power supply, it still provides a relatively high power-efficiency of 1. 26 GHz/mW. • An on-chip open-loop frequency and duty cycle controller (FDCC) is proposed. • The FDCC is compact, flexible, power efficient and suitable for academic prototyping. • The FDCC allows the simultaneous control of output frequency and duty cycle. • The FDCC architecture is implemented in 0.18& 0.35 μ m CMOS processes for validation. [ABSTRACT FROM AUTHOR]

The importance of active sonar is increasing due to the quieting of submarines and the increase in maritime traffic. However, the multipath propagation of sound waves and the low signal-to-noise ratio due to multiple clutter make it difficult to detect, track, and identify underwater targets using active sonar. To solve this problem, machine learning and deep learning techniques that have recently been in the spotlight are being applied, but these techniques require a large amount of data. In order to supplement insufficient active sonar data, methods based on mathematical modeling are primarily utilized. However, mathematical modeling-based methods have limitations in accurately simulating complicated underwater phenomena. Therefore, an artificial intelligence-based sonar signal synthesis technique is proposed in this paper. The proposed method modified the major modules of the Tacotron model, which is widely used in the field of speech synthesis, in order to apply the Tacotron model to the field of sonar signal synthesis. To prove the validity of the proposed method, spectrograms of synthesized sonar signals are analyzed and the mean opinion score was measured. Through the evaluation, we confirmed that the proposed method can synthesize active sonar data similar to the trained one. [ABSTRACT FROM AUTHOR]

Active electromagnetic interferences (EMI) cancellation is a promising solution to reduce the size of passive filters. Power electronic systems may generate periodic disturbances if they are controlled by periodic signals in steady-state operation. Periodic disturbances can be represented by a set of sine waves, according to the Fourier theory, and can be suppressed by an appropriate set of cancelling sine waves injected into the system. Since bothersome effects, like delay times or complex transfer functions, can be compensated by individually selecting the appropriate amplitude and phase for each cancelling sine wave, high EMI reductions can be achieved in a wide frequency range. In this contribution, this cancellation method is applied to the common-mode EMI of a three-phase motor inverter in stationary operation with periodic control signals in the frequency range from 150 kHz to 30 MHz. Approximately 2.4 million harmonics are suppressed. The characteristics of the overall system are discussed and the challenges for the cancellation system are elaborated. A method for the synthesis of the cancellation signal is introduced. The design of the cancellation system is described, and its signal processing is presented. The outstanding performance is proven by reference measurements in a laboratory setup. Extensions for practical applications are discussed. [ABSTRACT FROM AUTHOR]

High-quality brain signal data recorded by Stereoelectroencephalography (SEEG) electrodes provide clinicians with clear guidance for presurgical assessments for epilepsy surgeries. SEEG, however, is limited to selected patients with epilepsy due to its invasive procedure. In this work, a brain signal synthesis framework is presented to synthesize SEEG signals fromnon-invasive EEG signals. First, a strategy to determine the matching relation between EEG and SEEG channels is presented by considering both signal correlation and spatial distance. Second, the EEG-to-SEEG generative adversarial network (E2SGAN) is proposed to precisely synthesize SEEG data fromthe simultaneous EEG data. Although the widely adopted magnitude spectra has proved to be informative in EEG tasks, it leaves much to be desired in the setting of signal synthesis. To this end, instantaneous frequency spectra is introduced to further represent the alignment of the signal. Correlative spectral attention (CSA) is proposed to enhance the discriminator of E2SGAN by capturing the correlation between each pair of EEG and SEEG frequencies. The weighted patch prediction (WPP) technique is devised to ensure robust temporal results. Comparison experiments on real-patient data demonstrate that E2SGAN outperforms baseline methods in both temporal and frequency domains. The perturbation experiment reveals that the synthesized results have the potential to capture abnormal discharges in epileptic patients before seizures. [ABSTRACT FROM AUTHOR]

A method to reduce waveform distortion is proposed and experimentally verified for vibrators driven by voice coil motors. In this method, a current including high-order harmonics is synthesized to drive the vibrator. The amplitudes and phases of the high-order harmonics are calculated based on the measured parameters which are correlated with the distortion. These parameters include the displacement dependence of the vibrator stiffness and that of the magnetic force per unit current. The calculation model is built on the nonlinear vibrator dynamic equation. By minimizing the lower order harmonics of the output acceleration, a series solution is obtained to synthesize the driving current. The feasibility has been demonstrated by Simulink simulation. Applying this strategy to a home-made vibrator, the waveform distortion of vibration acceleration has been reduced from 9.60% to 1.22%. The proposed method provides an alternative technology to reduce the distortion. This technology is especially useful in case that it is difficult to reduce the nonlinearity of the vibrator.

Accelerometers and gyroscopes based on MEMS technology are promising for tracing motion in medicine, sport activities, human-machine interaction, robotics and many other areas due to the fact that they are self-containing and have a range of other advantages. Three orthogonally placed accelerometers and gyroscopes are combined into a single module fitted with a controller for processing the signals from inertial sensors. However, the same module may be suitable for one application and inapplicable for another, since the accuracy of tracking a motion trajectory depends not only on the error characteristics of the inertial sensors but also on the trajectory itself. Simulation may help decide whether an inertial measurement unit is a reasonable choice for a specific application or not. The idea is to allow the user to preset a desirable motion trajectory and error characteristics of the inertial sensors specified by their manufacturer. Then software simulates signals of real accelerometers and gyroscopes and computes a set of potential trajectories upon these signals. Upon the discrepancies between the prescribed and synthesized trajectories one can judge on applicability of the inertial sensors with the preset error characteristics for a specific task, without implementing a real device. The software should be based on well-known navigation equations, expressed via direction cosine matrices or quaternions. However, the equations are only valid for infinitesimal rotation angles. Their usage leads to cumulating errors in computation of some trajectories due to the fact that low-cost accelerometers and gyroscopes available on the market offer limited sample frequencies. The work reveals the problem related to usage of the above-mentioned equations, both analytically and by numerical experiments. Examples of trajectories irreproducible at low frequencies are shown. The work analyzes the reasons why some trajectories are irreproducible and shows that the reasons can scarcely be eliminated in case of rotation matrices. We have proposed amended equations universal for any trajectory and any sample frequency.

During the past decade, attacks by grey seals on fishing nets in the Baltic Sea have caused considerable loss of fish catch and damage to fishing gears. One of the approaches to reduce the number of seal attacks on fishing nets is to use acoustic deterrent devices (ADDs). Unfortunately, most of the commercially available ADDs are not well suited to the deployment in the sea and require considerable additional investments. The objective of the present research is to develop a compact and cost-efficient ADD for deployment in the sea environment. This paper is devoted to the design of acoustic signals for a prototype ADD. Signals from other experimental and commercially available ADDs are studied and compared. Moreover, limitations imposed by the underwater environment, transducers, battery power, and fish hearing are analysed and considered during the development of signal patterns. The results of tests conducted in an artificial reservoir and in the sea are presented.

Global navigation satellite Systems (GNSS) are highly susceptible to various interferences because of their inherent vulnerability. In these interferences, induced spoofing is very difficult to be detected because it can gradually drag off the tracking points without unlocking the tracking loops of the attacked receiver and cause the victim to obtain a wrong position and/or time information. Furthermore, it is also very difficult to generate induced spoofing data, including simulation data and real data, to evaluate various induced spoofing detection and suppression algorithms. Existing generation algorithms need to precisely control and adjust many parameters of GNSS simulation software even for simulation data. To address this problem, this study proposes a GNSS‐induced spoofing simulation algorithm based on path planning. First, through given planned paths, the proposed algorithm independently generates the authentic and spoofing signals without changing the parameters of GNSS simulation software. After that, the induced spoofing simulation data are synthesised by only adjusting the powers of authentic and spoofing signals. The effectiveness of the proposed algorithm is verified by the positioning solutions and the correlation function outputs of the code and carrier tracking loops. [ABSTRACT FROM AUTHOR]

Building up on classical linear formulations, we posit that a broad class of problems in signal synthesis and in signal recovery are reducible to the basic task of finding a point in a closed convex subset of a Hilbert space that satisfies a number of nonlinear equations involving firmly nonexpansive operators. We investigate this formalism in the case when, due to inaccurate modeling or perturbations, the nonlinear equations are inconsistent. A relaxed formulation of the original problem is proposed in the form of a variational inequality. The properties of the relaxed problem are investigated, and a provenly convergent block-iterative algorithm, whereby only blocks of the underlying firmly nonexpansive operators are activated at a given iteration, is devised to solve it. Numerical experiments illustrate robust recoveries in several signal and image processing applications. [ABSTRACT FROM AUTHOR]

The dual-mode auto-calibrating resistance thermometer (DART) has recently been proposed for highly accurate temperature measurement based on noise thermometry. In this paper, it is demonstrated that calibration and operation of the DART at part-per-million (ppm) level should be possible with the hardware developed. For this purpose, we have extensively tested a representative signal path comprising the basic DART components. This includes a low-noise amplifier connected to a 24-bit ÎŁ Î" ADC and a metrology-grade voltage reference. A Josephson arbitrary waveform synthesizer (JAWS) generates a pseudo-noise consisting of low-distortion multitones superimposed on a low-frequency square-wave reference voltage. Using this signal, a fast and efficient calibration scheme for the signal path gain is demonstrated. The reference voltage stabilizes the gain at ppm level. We observed gain fluctuations within ± 2 ÎĽ V V âˆ' 1 over a period of 19 d, a temperature coefficient of âˆ' 0.5 ÎĽ V V âˆ' 1 K âˆ' 1 , and insignificant nonlinearity within an uncertainty band of ± 2 ÎĽ V V âˆ' 1 for rms input levels between 5 µV and 80 µV. The behavior of the signal path with a 300 Ω resistor as a noise source was also investigated. From the observed stability of the voltage reference and flatness of the noise gain between 10 kHz and 225 kHz, we estimate that the presented hardware components are suitable for temperature measurements with systematic uncertainties well below 10 ÎĽ K K âˆ' 1 . [ABSTRACT FROM AUTHOR]

Dynamic-Contrast-Enhanced (DCE) Imaging has been widely studied to characterize microcirculatory disorders associated with various diseases. Although numerous studies have demonstrated its diagnostic interest, the physiological interpretation using pharmacokinetic models often remains debatable. Indeed, to be interpretable, a model must provide, at first instance, an accurate description of the DCE data. However, the evaluation and optimization of this accuracy remain rather limited in DCE. Here we established a non-linear Free-Time-Point-Hermite (FTPH) data-description model designed to fit DCE data accurately. Its performance was evaluated on data generated using two contrasting pharmacokinetic microcirculatory hypotheses (MH). The accuracy of data description of the models was evaluated by calculating the mean squared error (QE) from initial and assessed tissue impulse responses. Then, FTPH assessments were provided to blinded observers to evaluate if these assessments allowed observers to identify MH in their data. Regardless of the initial pharmacokinetic model used for data generation, QE was lower than 3% for the noise-free datasets and increased up to 10% for a signal-to-noise-ratio (SNR) of 20. Under SNR = 20, the sensitivity and specificity of the MH identification were over 80%. The performance of the FTPH model was higher than that of the B-Spline model used as a reference. The accuracy of the FTPH model regardless of the initial MH provided an opportunity to have a reference to check the accuracy of other pharmacokinetic models. [ABSTRACT FROM AUTHOR]

Information and communication systems (ICSs) must comply with increasingly stringent requirements to ensure the reliability and speed of information transmission, noise immunity, information security. This paper reports the methods to synthesize discrete complex cryptographic signals, underlying the construction of which are random (pseudo-random) processes; the methods for synthesizing characteristic discrete complex signals whose construction is based on using the nature of the multiplicative group of a finite field; the results of studying the properties of the specified signal systems. It is shown that the methods built provide a higher synthesis performance than known methods and make it possible to algorithmize the synthesis processes for the construction of software and hardware devices to form such signals. The win in the time when synthesizing nonlinear signals in finite fields using the devised method is, compared to the known method, for the period of 9,972 elements is 1,039.6 times. The proposed method for synthesizing the entire system of such signals, based on decimation operation, outperforms the known method of difference sets in performance. Thus, for a signal period of 2,380 elements, the win in time exceeds 28 times. It has also been shown that the application of such systems of complex signals could improve the efficiency indicators of modern ICSs. Thus, the imitation resistance of the system, when using complex discrete cryptographic signals with a signal period of 1,023 elements, is four orders of magnitude higher than when applying the linear signal classes (for example, M-sequences). For a signal period of 1,023 elements, the win (in terms of structural secrecy) when using the signal systems reported in this work exceeds 300 times at a period of 8,192, compared to the signals of the linear form (M-sequences). [ABSTRACT FROM AUTHOR]

Inductive wear debris sensor has been proved to be an effective device for lubricant oil condition monitoring and fault diagnosis. However, the narrow internal diameter of current sensing coil, designed for high sensitivity, limits the oil throughput. To improve the throughput without sacrificing the sensitivity, a novel multichannel wear debris detection method based on time division multiplexing is presented in this work. Only one excitation signal is used to excite multiple sensing coils. Then, the signals from multiple sensing coils are combined with a serials of square waves separately, which are self-designed specially. As a result, the peak waveforms are lifted in different timeslots by the high-level voltages in squares waves. After that, the peaks of the signals are cut out and combined into one output signal. Then, we used synchronized sampling method to record the peak values of the output signal. The signals for all sensing channels are finally extracted from the recorded peak values. To validate the feasibility of the proposed method, we designed a ten-channel sensor system using time division multiplexing. Through the pseudo-dynamic and dynamic test, it is proved that the sensor could detect wear debris in different channels simultaneously and independently without sacrificing the sensitivity. In addition, the proposed method has the potential to integrate more channels into one system, which would contribute to high throughput real time lubricant oil detection. [ABSTRACT FROM AUTHOR]

We designed, simulated, and experimentally demonstrated components for a microwave-frequency digital-to-analog converter based on single flux quantum (SFQ) circuits and an amplifier based on superconducting-quantum-interference-device (SQUID) stacks. These are key components for a self-calibrated programmable waveform reference for communications metrology capable of synthesizing high-frequency signals with quantum-based output accuracy. The amplifier is an SFQ voltage multiplier circuit that consists of a network of SFQ-splitters and SQUID transformers that provides output signals consisting of quantized pulses. The circuits were fabricated using our Nb/Nbx Si1-x/Nb Josephson-junction (JJ) fabrication process, which produces self-shunted JJs with Nb-doped silicon barriers. In order to demonstrate quantum-based reproducibility, stability and performance at 4 K, we synthesized single-tone and multitone waveforms at gigahertz frequencies and demonstrated their operation over a range of synthesizer output and experimental bias parameters. We also propose circuit designs for achieving higher synthesis frequencies and higher output power with improved power accuracy and spectral purity, and discuss the potential limitations of these circuits. [ABSTRACT FROM AUTHOR]

In spite of the challenges associated with obtaining actual PMU measurements for research purposes and analytic methods testing, it remains crucial that experimental input data exhibits similar quality features of real measurements for proper grid assessment and planning. The objective of this paper is to generate and validate large sets of synthetic, but realistic, PMU datasets obtained from complex grid models. A study of different variability components in PMU measurements is first presented followed by the proposed steps in generating synthetic datasets. Random variations of resource inputs are used in a simulation platform to generate prior voltage data from a synthetic 2,000-bus system, followed by a data modification process to infuse further realism into the dataset. The validation process used to assess the accuracy of the generated voltage dataset utilizes a variability metric to determine the level of inherent variations in individual measurements, and further applies a dimension reduction technique to identify the extent of electrical dynamics retained in the overall synthetic dataset. [ABSTRACT FROM AUTHOR]

We present a new Randomized Multiple Independent Comb Shaping (RandoMICS) algorithm based on phase-only tailored transmission for ultrashort laser pulse replication. The benefit of this method is satellite-free generation of programmable laser pulse sequences. The result is achieved by creating a transmission function as a stochastic comb of disjoint segments of optical frequency continuum with numerically optimized segment width distribution. The algorithm is realized by generating a regular aperiodic comb and random permutations of its elements. Experimental demonstration is performed with an acousto-optic pulse shaper providing broadband multi-window transmission function with arbitrarily variable widths of the segments. Suppression of undesired satellite pulses by the factor of 8 is demonstrated as well as generating pulse replicas with extended usable delay range compared to phase-only pulse shaping with periodic transmission combs. [ABSTRACT FROM AUTHOR]

Random phase multisines tend asymptotically, with an increasing number of harmonics and irrespective of their spectral coloring, to the Gaussian amplitude distribution and can be used as an alternative to Gaussian signals to measure the best linear approximation (BLA) of nonlinear systems. The asymptotic error on the measured frequency characteristics, compared to that measured with Gaussian noise, is of order $O(M^{-1})$ , where $M$ is the number of harmonics. Flat (white) multisines are still a better approximant to Gaussian noise, because even in a nonasymptotic setting ($M$ is low), the measured BLA of a static nonlinearity remains static. This is due to the fact that both Gaussian noise and flat random phase multisines are separable signals. Random phase multisines with a nonflat spectral coloring, however, are nonseparable signals and introduce dynamics to the BLA of a static nonlinearity, which was observed for a low harmonic number. Due to this reason, usually, only flat random phase multisines are used in the applications. In this paper, we investigate more deeply this phenomenon, performing an order $O(M^{-2})$ analysis of the approximation error. We show that the dynamics of the error depend, in a simple way, on the spectral coloring and this effect is decaying quickly with increasing $M$. We conclude, in consequence, that colored random phase multisines are asymptotically a good working alternative to Gaussian noise and even a better choice for an excitation than flat random phase multisines due to more freedom in a signal design. [ABSTRACT FROM AUTHOR]

This article proposes a method for the measurement of phase noise (PN, or PM noise) and amplitude noise (AN, or AM noise) of digital-to-analog converters (DACs) and direct digital synthesizers (DDSs) based on the modulation-index amplification. The carrier is first reduced by a controlled amount (30–40 dB) by adding a reference signal of nearly equal amplitude and opposite in phase. Then, residual carrier and noise sidebands are amplified and sent to a conventional PN analyzer. The main virtues of our method are: 1) the noise specs of the PN analyzer are relaxed by a factor equal to the carrier suppression ratio and 2) the capability to measure the AN using a PN analyzer with no need for the analyzer to feature AN measurement. An obvious variant enables AN and PN measurements using an AN analyzer with no PN measurement capability. Such an instrument is extremely simple and easy to implement with a power-detector diode followed by an FFT analyzer. Unlike the classical bridge (interferometric) method, there is no need for external line stretcher and variable attenuators because phase and amplitude controls are implemented in the device under test. In one case (AD9144), we could measure the noise over 10 decades of frequency. The flicker noise matches the exact $1/f$ law with a maximum discrepancy of ±1 dB over 7.5 decades. Due to the simplicity, reliability, and low background noise, this method has the potential to become the standard method for the AN and PN measurements of DACs and DDSs. [ABSTRACT FROM AUTHOR]

Behavior models of electronic components are critical in many metrological and measurement areas, e.g., time-domain simulations for analog-integrated circuit design and predistortion of the amplifier to reduce the distortion. This paper describes the use of pulse-driven ac Josephson voltage standard (ACJVS) to synthesize quantum accurate waveforms with ultralow distortion and noise floor to model the amplifier nonlinearity, which is a promising way to increase the modeling accuracy. Four Volterra series models including the memory polynomial model and three submodels of the dynamic deviation reduction model are analyzed and compared in detail. Normalized mean square error is calculated to evaluate the modeling accuracy. The difference of the measured and predicted outputs of the amplifier are compared in both time and frequency domains. The result shows that high-performance models can be achieved, which demonstrates the feasibility of modeling nonlinear amplifier behavior with the ACJVS. [ABSTRACT FROM AUTHOR]

This paper describes the implementation of a sampling wattmeter for the measurement of active and reactive power over the 50-Hz–6-kHz frequency range, 20–600-V voltage range, and 0.05–80-A current range. The wattmeter is capable of measuring sinusoidal and distorted voltage and current signals with up to 100 harmonics of the fundamental frequency component. Details of the system design, measurement techniques, and significant sources of uncertainty are presented. [ABSTRACT FROM AUTHOR]

Intelligent fault diagnosis, particularly via data-driven deep learning, is vital for industrial health management. However, it often faces challenges due to unbalanced datasets, with either insufficient fault data or redundant data representing the same condition. For signal-based diagnosis, generative adversarial networks (GANs) provide a countermeasure by generating new signals for data augmentation but can suffer from mode collapse, causing monotonous new signals and further imbalance. Inspired by the conditional mechanism, we propose mode standardization to mitigate mode collapse in GAN-based signal synthesis. This method utilizes part of the original signals as reference input to the generator. As a result, although mode collapse still occurs, and the new signals may still be monotonous, this monotony is confined to their references. In other words, as long as the references are diverse, the generated signals will maintain an acceptable diversity, similar to the original. The negative effects of mode collapse are diminished, decreasing harm to the generation process. Comparative experiments demonstrate mode standardization's effectiveness in diversity and quality on various datasets, affirming it as a practical countermeasure against mode collapse and a suitable strategy for industrial practice. • A method countering GAN's mode collapse in signal synthesis. • Compensation deployed for quality decrease in mode collapse countermeasures. • Diversity can be acquired during mode collapse. • A practical method can get higher diversity without complicated modification. [ABSTRACT FROM AUTHOR]

This paper introduces Con-GAN, an innovative improvement of GAN-based data augmentation designed to address data insufficiency in fault diagnosis methodologies. Distinctly different from traditional GAN-based data augmentation, Con-GAN aims to generate realistic continuations of existing signals and subsequently integrates these continuations with the original signals. This 'real-fake-mixed' strategy fully leverages the existing signals and results in high-quality new signals for data augmentation, making our approach both safer and more effective. With rigorous validation across multiple datasets, which include both artificially induced and test-caused real faults, Con-GAN's consistent effectiveness has been substantiated. Compared to other GANs, Con-GAN presents distinct advantages, yielding new signals with better validity and variety. In summary, Con-GAN introduces a novel and feasible paradigm in GAN-based data augmentation, demonstrating practical value for industrial. In the future, we plan to evaluate Con-GAN's performance under conditions with high noise levels, exploring its robustness and adaptability across a wider range of scenarios. • This paper proposes Con-GAN for generating signals not existing in original datasets to alleviate data insufficiency. • Con-GAN generates the continuation of the original signals and merges them with the originals to form new signals. • A rough measurement of the information capacity of vibrational signal datasets, Range of Sampling (RS), is proposed. [ABSTRACT FROM AUTHOR]

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Ultrasonic testing systems are widely used for the analysis and characterization of materials. In many applications, such as ultrasonic imaging and spectroscopy, wide bandwidth, spectral flatness, and signal-to-noise ratio (SNR) are essential. The transfer function of the ultrasonic transducer is the bandwidth limiting factor. Pulse excitation has limitations in spectral coverage and achievable SNR. Spread spectrum (SS) signals combined with amplitude modulation are used to compensate the spectral losses and widen the bandwidth. Yet, SS signals require arbitrary waveform generation using digital-to-analog converters and linear power amplifiers, resulting in costly, large, and inefficient equipment. To overcome the aforementioned problems, we propose the use of bipolar arbitrary position and width pulses (APWP) sequences derived from nonlinear frequency modulated SS signals. APWP are obtained by an iterative optimization for the spectral flatness and bandwidth of the received signal. Comparisons of the proposed signals with known linear and nonlinear modulation signals are shown in terms of bandwidth and spectral flatness. [ABSTRACT FROM AUTHOR]

The design of a directional modulation (DM) signal by a phased array is one of the important topics in the field of physical layer security communication. In this paper, we synthesize a sparse array for DM based on convex optimization. The main idea is that a nonconvex optimization problem associated with $\ell _{0}$ -norm is formulated for synthesizing a sparse array. To solve this nonconvex optimization problem, two different solutions are employed to relax the nonconvex optimization problem in a convex way: one is based on iterative reweighted $\ell _{1}$ -norm resulting in a superdirective array, the other is based on mixed integer programming resulting in a nonsuperdirective array. Furthermore, multiple important metrics of a DM transmitter, such as power efficiency, information beamwidth, and dynamic DM signal, are also considered in the optimization problem to achieve better performance of the DM signal via a sparse array. Simulation results show that the proposed synthesis method provides greater flexibility of controlling the security performance, power efficiency, and static or dynamic DM signal while the number of excitations is less than the uniformly spaced linear array in the benchmark problems. [ABSTRACT FROM AUTHOR]

A coherent additional signal whose zero side-lobe region (its relative width lies in the interval [1 3,1)) is located near the central peak of an aperiodic autocorrelation function is synthesized. It is demonstrated that the given signal is the batch composed of two phase-shift keyed pulses encoded by paired or adjacent sequences of the D-code with the length N = 2k signal synthesis is proposed to generate from a set of the N/4 ensembles of D-code with length N. The correlation characteristics of the synthesized signal are analyzed. [ABSTRACT FROM AUTHOR]

Target position estimation of radar system has attracted much attention. Researchers have proposed a variety of joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation algorithms over the last few decades for this well-known problem. However, traditional estimation algorithms require a pairing process between the DOD and DOA estimation. In this study, the authors propose an improved unitary estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm for joint DOD and DOA estimation without a pairing operation. The waveforms are transmitted by an array with M sensors and received by two detached sub-arrays with N1 and N2 sensors, respectively. Specifically, the proposed algorithm eliminates a pairing process via sharing the eigenvectors of DOD and DOA. Theoretical derivation demonstrates that the proposed algorithm requires less computational complexity than two-dimensional multiple signal classification (MUSIC), reduced-dimension MUSIC, and ESPRIT. Simulation results show that the proposed algorithm can effectively enhance the accuracy of identifying and locating targets for the bistatic multiple-input multiple-output radar system. [ABSTRACT FROM AUTHOR]

Problem: The development of the placenta and its functions are sensitive to infection and stress, which can activate the hypothalamic‐pituitary‐adrenal axis. Adrenally produced glucocorticoids are the body's primary mediators of the inflammatory and stress response. Although the glucocorticoid receptor (GR) is expressed in all human villous trophoblast tissue, the effect of glucocorticoids on placentation is not well understood. Method of study: Using microarray analysis, we identified the glucocorticoid‐regulated transcriptional profile in the immortalized first‐trimester extravillous trophoblast cell line Swan.71 (Sw.71). Results: The synthetic glucocorticoid dexamethasone significantly regulated 3829 genes, including genes associated with cell movement, growth, and survival. SERPINE1, an inhibitor of trophoblast invasion, was induced by glucocorticoids in Sw.71 cells and is associated with the pathogenesis of preeclampsia. Glucocorticoid treatment induced recruitment of activated polymerase II and GR to the SERPINE1 promoter, suggesting a mechanism for transcriptional regulation. Functionally, glucocorticoid treatment inhibited cell proliferation, migration, and invasion. Conclusion: These findings suggest that glucocorticoids regulate extravillous trophoblast functions by altering the gene expression profile, which may contribute to the pathogenesis of reproductive disorders such as preeclampsia and IUGR. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of generating unmeasured kinetic data-and/or providing improvements in existing data-for the enhancement of performance characteristics of earthquake engineering test systems, such as shaking tables, reaction walls and other custom-made test rigs. The approach relies upon the use of composite filters (CF), a method of data fusion that was originally conceived via transfer function formulation. The current work generalises the CF concept and extends its formulation into the state-space domain, thereby providing a wider basis for application to test systems and their controllers, including those of a multivariable (coupled, multi-axis) nature. Comparative simulation studies of shaking table control are presented that demonstrate the design techniques for state-space CF and also their effectiveness for signal synthesis, noise suppression and performance improvement. Specific examples include the use of CF for displacement demand signal generation, velocity feedback generation and acceleration control. In each case, the essential principles behind CF-output signals with zero bias and zero drift-are consistently upheld. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]