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Both siamese network and correlation filter (CF)-based trackers have exhibited superior performance by formulating tracking as a similarity measure problem, where a similarity map is learned by the correlation between a target template and a region of interest (ROI) with a cosine window. Nevertheless, this window function is usually fixed for various targets and not changed, undergoing significant noise variations during tracking, which easily makes model drift. In this article, we focus on the study of a noise-aware (NA) framework for robust visual tracking. To this end, the impact of various window functions is first investigated in visual tracking. We identify that the low signal-to-noise ratio (SNR) of windowed ROIs makes the above trackers degenerate. At the prediction phase, a novel NA window customized for visual tracking is introduced to improve the SNR of windowed ROIs by adaptively suppressing the variable noise according to the observation of similarity maps. In addition, to further optimize the SNR of windowed pyramid ROIs for scale estimation, we propose to use the particle filter to dynamically sample several windowed ROIs with more favorable signals in temporal domains instead of this pyramid ROIs extracted in spatial domains. Extensive experiments on the popular OTB-2013, OTB-50, OTB-2015, VOT2017, TC128, UAV123, UAV123@10fps, UAV20L, and LaSOT datasets show that our NA framework can be extended to many siamese and CF trackers and our variants obtain superior performance than baseline trackers with a modest impact on efficiency.

Propagating plane-wave fast multipole translation operators (TLOPs) convert propagating plane-wave spectra radiated from a source region of finite extent into incident propagating plane-wave spectra at a distant observation region of finite extent. This translation is diagonal, and the received fields in the observation region are obtained by integration of the received plane-wave spectra. In its standard form, the TLOPs exhibit some directivity but with strong sidelobes and the integration needs to consider the entire spectra. Windowed and Gaussian-beam (GB) TLOPs with improved directivity and reduced sidelobes have been considered in order to reduce the integration effort. Both these techniques are investigated in this article, and it will be demonstrated that GB TLOPs are considerably more powerful. It is shown that GB TLOPs can be interpreted as windowed TLOPs, where a complex windowing function is multiplied with the Legendre polynomial series coefficients of the standard TLOPs. The sampling requirements of the GB TLOPs are investigated, and a numerical procedure is presented for an error-controlled determination of the imaginary shift involved in the computation of the GB TLOPs and their orders. Numerical results obtained with an inverse source solver for several antennas with aperture sizes of up to 1000 wavelengths are presented.

In order to overcome the problems of the traditional algorithm, such as the time-consuming execution of acquisition instructions, low signal tracking accuracy, and low signal capture accuracy, a global satellite positioning receiver acquisition and tracking algorithm based on UWB technology is designed in this study. On the basis of expounding the pulse generation method and working principle in UWB technology, this paper analyzes in detail the characteristics of UWB technology, such as antimultipath, low power consumption, and strong penetration. Then, on the basis of window function filtering, in the process of three-dimensional search of global satellite positioning signal, firstly, the satellite signal entering the GPS software receiver is processed by RF front-end mixing and AD sampling, and then, the signal tracking and navigation message solving are completed according to the relationship between the influence factor and Doppler frequency offset. The experimental results show that the execution time of the acquisition instruction of the proposed algorithm varies between 1129 ms and 1617 ms; the signal tracking accuracy ranges between 0.931 and 0.951, and the signal capture accuracy ranges between 93.3% and 95.6%, which proves that the proposed algorithm has achieved the design expectation.

Building on past work showing that the Hilbert transform can be used for edge feature enhancement, a new edge feature enhancement method is developed using a two‐dimensional (2D) isotropic Hilbert transform of the Cauchy distribution. First, both the shape of the Hilbert kernel and the Hilbert transform of edge feature models (step and delta) and various simulated signals result in edge feature enhancement, the properties of which are derived and confirmed. Second, Cauchy distribution as low‐pass filter is introduced in Hilbert transform to get new edge feature enhancement operator, and its efficiency under various criteria is comprehensively discussed. Third, a 2D isotropic extension is presented using a circularly symmetric window function. Finally, two experiments, including edge detection and image segmentation, are performed to validate the proposed edge feature enhancement method. The experimental results of the method applied to the Berkeley Segmentation Dataset and remote sensing images demonstrate that the new method is effective for edge detection and image segmentation.

While traditional edge detectors concentrate on modifying the shape of the window function, we consider the edge detection problem from a new perspective, and an effective recurrent guidance filter is proposed in this letter. The proposed filter is elaborately designed for edge detection tasks and aims to remove the nonedge information including speckle noise and detailed texture and preserve edge information simultaneously. We first filter the image by the proposed filter and a filtered image is obtained. Then, by using the edge detector with the Gaussian-shaped window, which was previously proposed by us and performing the postprocessing method, the edge response is extracted from the filtered image. Both objective and subjective experimental results on simulated and real synthetic aperture radar (SAR) images demonstrate that the edge detector based on the recurrent guidance filter yields better performance than the state-of-the-art edge detectors.

The problem of synthesis of low-order polynomial window functions with an arbitrarily specified decay rate of spectral lobes (optimal with respect to minimization of the maximum side lobe on a specified segment of the frequency axis) is solved. A method for the synthesis of optimal functions with verification of the solution is developed. The window functions of orders 1–12 with side-lobe decay rates of 6, 12, 18, 24, and 30 dB/oct are synthesized and tables of the parameters are presented. The characteristics of the functions are analyzed and compared with the known ones. A simple algorithm for calculation of the synthesized functions is proposed.

In this letter, we propose a method of monitoring driver's movement using a small-sized millimeter-wave radar sensor. First, we install a frequency-modulated continuous wave radar sensor on the steering wheel and collect reflected signals for various driver motions. Because the reflection patterns are different for each motion, we can distinguish different movements of the driver by analyzing the received signal. In our method, we use the spectrogram of the received signal obtained through multiple measurements and apply a window function to extract the radar signal in the form of an image. Then, we use the convolutional neural network architecture to classify the radar signal images. The classification results show that our proposed method can classify four different movements of the driver with an accuracy higher than 80%.

This article presents a new fine Doppler frequency estimation method of complex sinusoidal signals for radar systems. The proposed method can work with nonrectangular window functions to suppress the interference signal caused by the undesired spectral leakage. This method is based on an interpolation curve that uses the sum and difference of two discrete Fourier transform (DFT) magnitudes, and can estimate an accurate frequency between the interpolation curve samples through precise linear approximation. The proposed method exhibits lower computational complexity than the conventional method, which compensates the bias of an arbitrary window function and exhibits high performance. Thus, the proposed method is applicable to radar systems requiring fast processing time. Furthermore, the simulation results show that the proposed method outperforms the conventional method for various window functions.

In this paper, the Cauchy mixture distribution is used for rigid and affine registration. The Cauchy function has a wider effective range than the general window function, so it has a greater information utilization ratio than most registration algorithms. This means that the method can quickly match point clouds without initial registration and corresponding points. On the other hand, the computational complexity of Cauchy mixture model is lower than that of widely used Gaussian mixture model. This means that the introduction of Cauchy mixture model will save computing resources. However, the log-likelihood function of the Cauchy mixture distribution is a nonlinear function that is difficult to solve. This paper proposes an optimization method for the Cauchy mixture model, and discusses the advantages of the Cauchy mixture model in rigid and affine registration. In the experiment, compared with several other algorithms, our method quickly and accurately registers point clouds.

Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here, we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absence in memristors described by the Joglekar window function, when such memristors are driven by periodic alternating polarity pulses. It is anticipated that the results of this brief will contribute toward the development of more sophisticated models of memristive devices and systems.

Windowing digital signals is essential to digital signal processing. The matter is a complicated one, and choosing a window function is always a tradeoff between certain undesired effects on one hand and important benefits on the other. In this article, a new window class of windows called sine ramp windows is presented, which is very fast decaying with regard to the frequency resolution. These new windows improve the attenuation of far-distant spectral leakage while maintaining an acceptable minimal signal duration, which is beneficial, e.g., in the harmonic analysis of power systems in transient conditions. This window class is then extensively benchmarked against the state of science using common figures of merit proving its advantages, which are then shown in two application examples.

Time–frequency (TF) analysis (TFA) provides an effective tool to characterize nonstationary signals with time-varying features. However, the TFA of gas turbine’s vibration signals is a challenging topic due to high complexity and strong nonstationarity. There is an obstacle to generate more accurate and sharper TF results for such multicomponent signals. This article proposes a novel TFA technique, named local maximum synchrosqueezing chirplet transform (LMSSCT), to deal with this problem. This method can not only well match window function and modulated frequency but produce an unbiased instantaneous frequency (IF) estimator to correct the deviation caused by strong frequency modulation (FM) in TF results. We give the theoretical analysis that this method is an improvement of classical local maximum synchrosqueezing transform (LMSST), and we also prove that it allows for perfect signal reconstruction. The numerical validation shows that the proposed method can be employed to effectively address the multicomponent signals with complex FM laws, even those with heavy noise. The experimental analysis on the test-bench signal and the vibration signal of a dual-rotor gas turbine validates that this method can capture more detailed features that are helpful to identify the origins of abnormal vibration of gas turbine.

In this paper, a low-complex chip to extract the Mel Frequency Cepstral Coefficient for a speech recognition system is presented. The architecture can operate in a continuous-flow manner to process streaming or the stored speech signal at high speed. The frame-overlap Hamming window, DFT and Mel-filter bank computations are deeply integrated to share memory buffers and avoid bit-reversal circuit to reduce area and latency. Moreover, normalised energy consumption and area delay product are reduced by 32%, and speed is increased by 5.2 times compared to prior works. Further, the fixed-point word-length is optimised to minimise the area without affecting the accuracy.

This article proposes a method of phasor estimation called the Morlet wavelet-based two-point finite-impulse response (FIR) filter (MW-FIR), showing advantages on algorithm complexity, customizability, and zero overshoot. The method focuses on amplitude and frequency estimation, while phase and rate of frequency of change (ROCOF) estimation can be performed using the standard signal processing model with an FIR filter. The mathematical principle behind the method is presented. The causes of error are discussed, and the parameter selection procedure is introduced to minimize error and adjust algorithm performance according to different application requirements. The proposed method has been discussed and compared with the three-point interpolated discrete Fourier transform (ipDFT) method and the FIR method using a flat-top (FT) windowing function, under the static and dynamic situations given by the IEC/IEEE 60255-188-1 and noise immunity evaluation. Finally, the major advantages of the proposed frequency estimation method compared with the conventional FIR-based method using the derivative of angular position are discussed. It can be concluded that this method becomes a substitute for ipDFT in most cases and shows several advantages over the FIR-based method with an FT sequence.

Windows such as Dolph-Chebyshev window and Kaiser window are adjustable, whereas windows such as Hamming window and Blackman window are traditionally not adjustable. In [1], a technique for trading off main lobe width against sidelobe magnitude for any arbitrary window, including the traditionally non-adjustable windows, was presented. However, the method in [1] requires a large number of iterations if the specification is very tight. Developed based on a new perspective on the window adjustment principle, a new method to achieve the same adjustment capability as in [1], but at a very much fewer iterations is presented in this letter. Our new method is particular useful if the specification is very tight.

This paper considers the designs of the periodic window functions in the filter window banks. First, the filter window bank with the constant synthesis periodic window functions is considered. The total number of the nonzero coefficients in the impulse responses of the analysis periodic window functions is minimized subject to the near perfect reconstruction condition. This is an \begin{document}$ L_0 $\end{document} norm optimization problem. To find its solution, the \begin{document}$ L_0 $\end{document} norm optimization problem is approximated by the \begin{document}$ L_1 $\end{document} norm optimization problem. Then, the column of the constraint matrix corresponding to the element in the solution with the smallest magnitude is removed. Next, it is tested whether the feasible set corresponding to the new \begin{document}$ L_0 $\end{document} norm optimization problem is empty or not. By repeating the above procedures, a solution of the \begin{document}$ L_0 $\end{document} norm optimization problem is obtained. Second, the filter window bank with the time varying synthesis periodic window functions is considered. Likewise, the design of the periodic window functions in both the analysis periodic window functions and the synthesis periodic window functions is formulated as an \begin{document}$ L_0 $\end{document} optimization problem. However, this \begin{document}$ L_0 $\end{document} norm optimization problem is subject to a quadratic matrix inequality constraint. To find its solution, the set of the synthesis periodic window functions is initialized. Then, the set of the analysis periodic window functions is optimized based on the initialized set of the synthesis periodic window functions. Next, the set of the synthesis periodic window functions is optimized based on the found set of the analysis periodic window functions. Finally, these two procedures are iterated. It is shown that the iterative algorithm converges. A design example of a filter window bank with the constant synthesis periodic window functions and a design example of a filter window bank with the time varying synthesis periodic window functions are illustrated. It is shown that the near perfect reconstruction condition is satisfied, whereas this is not the cases for the nonuniform filter banks with the conventional samplers and the conventional block samplers.

In recent years, there have been increased demands for aggregating sensor information from several sensors owing to the spread of the Internet of Things (IoT). However, packet communication, which is a conventional multiple-access technology, is hindered by packet collisions owing to simultaneous access by sensors and waiting time to avoid packet collisions; this increases the aggregation time. The physical wireless parameter conversion sensor network (PhyC-SN) method, which transmits sensor information corresponding to the carrier wave frequency, facilitates the bulk collection of sensor information, thereby reducing the communication time and achieving a high aggregation success rate. However, when more than one sensor transmits the same frequency simultaneously, the estimation accuracy of the number of accessed sensors deteriorates significantly because of multipath fading. Thus, this study focuses on the phase fluctuation of the received signal caused by the frequency offset inherent to the sensor terminals. Consequently, a new feature for detecting collisions is proposed, which is a case in which two or more sensors transmit simultaneously. Furthermore, a method to identify the existence of 0, 1, 2, or more sensors is established. In addition, we demonstrate the effectiveness of PhyC-SNs in estimating the location of radio transmission sources by utilizing three patterns of 0, 1, and 2 or more transmitting sensors.

In order to select the window function and window size adaptively before getting the results, we proposed adaptive moving window principle component analysis (AMWPCA) based OMA method to identify modal shapes and modal natural frequencies of slow LTV structures with weekly damped only from non-stationary vibration response signal online. The adaptive is achieved in two ways: change the window function or window size. We develop an adaptive indicator as the basis for window function and window size changes. Our adaptive approach is to make the difference between adjacent eigenvalues not too small. The operational modal parameter identification results in non-stationarity response signal dataset of a three-degree-of-freedom structure with slow time-varying mass show that comparing with fixed size moving window principle component analysis, our AMWPCA method can identify the modal shapes and modal frequencies better.

Resampling technology is becoming increasingly critical, as different frequency components are required to be measured in one device. In this paper, a resampling method based on filter designed by window function is proposed to satisfy the requirements of different sampling rates. The frequency responses of the filter in the resampling model based on the Farrow structure are investigated, and the design criterion of the filter in the resampling model is proposed. A fractional delay filter design model based on window function method is established. A fractional delay filter coefficient matrix, which is expressed by a polynomial form, is constructed. Then, the expression related to the subfilter coefficients is obtained and subfilter coefficients are solved by the least-square method. The simulation results show that the filter designed by the proposed method has better performance when used for resampling as compared those designed by existing methods, and can efficiently prevent the occurrence of frequency aliasing and mirroring components in the process of sampling rate conversion. Therefore, the proposed method meets the conditions for application to existing measurement devices.

The fault model of the inter-turn short circuit of the dry air-core reactor is first analysed in this study, by which an online monitoring method of the reactor inter-turn insulation fault is proposed by using the change of the power angle. In order to achieve high-precision measurement, the fundamental harmonic separation algorithm improved by Hanning windowed interpolation method can effectively reduce the error of power angle measurement caused by frequency fluctuation and harmonic interference. By comparing it with the power angle measurement errors of fast Fourier transform (FFT) and Hanning window interpolation FFT, the algorithm is verified. The sensitivity and stability of the equipment are verified by the experiment of simulating and eliminating the fault in the initial stage of the inter-turn short circuit. At the same time, an online monitoring system for inter-turn insulation fault of dry-type air-core reactor based on this method is designed, including field monitoring device, the intelligent electronic device of the dry air-core reactor and expert software. The method and monitoring device proposed in this study enables the fault to be accurately monitored in the early stage, which is of great significance for the safe operation of the reactor.

Frequency diverse array (FDA) is capable of generating a range-angle-dependent beampattern via adjusting the frequency offset across array elements. The classical linear FDA generates an S-shaped beampattern due to the range-angle-dependent coupling. In order to remove the coupling, and obtain a well-focused dot-shaped beampattern, several FDA frameworks are proposed via adjusting frequency offsets. It seems that the window based tapering frequency offsets are able to form a single maximum with a satisfactory mainbeam sharpness. However, most window-based FDA schemes are focused on classical fixed windows. In this letter, an FDA framework with Taylor windowed frequency offsets is first proposed. Considering that adjustable tapering windows allow adjustments by parameter manipulation, the optimized parameters of the window function are determined. The FDA beamforming results with all kinds of frequency offsets are measured, and compared. Numerical results validate the superiority of proposed FDA in terms of mainlobe width, and sidelobe level.

Delay diversity (DD) is a low-complexity and flexible transmit diversity technology for coded offset quadrature amplitude modulation based filter bank multicarrier (OQAM/FBMC) transmission systems. However, the introduction of delay parameters in DD-OQAM/FBMC systems leads to increased channel frequency selectivity, which makes the channel estimation problem more complicated. In this paper, we analyze and develop preamble-based channel estimation methods in DD-OQAM/FBMC systems from the perspective of frequency-domain, transform-domain, and time-domain aspects. Besides, channel estimators that can obtain the minimum channel estimation mean square error under least squares (LS) and linear minimum mean square error (LMMSE) criteria are derived according to different levels of channel knowledge. Specifically, the proposed frequency-domain method estimates each channel frequency response individually based on a simplified frequency-domain channel model. The transform-domain method first estimates the equivalent single-input-single-output channel observed at the receiver assuming subchannel flatness, and then uses a window function in the time domain to separate the channels of different transmit antennas. The time-domain method is constructed based on an accurate time-domain channel model to directly estimate the channel impulse response without making any assumption about the subchannel flatness. A series of simulation experiments is conducted to verify the effectivity of these channel estimation methods for DD-OQAM/FBMC systems.

In this article, dual-sided permanent magnet linear motors (DPMLM) have been wildly applied in linear motion occasions such as high-precision laser cutting machines. This article researches a new way for accurate demagnetization fault detection of DPMLM, and this proposed method based on signal enveloping and time-domain energy analysis can be suitably used in some typical industrial occasions such as motor batch demagnetization inspection before delivery and periodic maintenance. First, three magnetic signals in motor air-gap region are selected as demagnetization fault index, and finite element analysis (FEA) is used to obtain these signals. Second, complex continuous wavelet transform (CCWT) is introduced to preprocess the fault signal and extract signal envelop for next-step fault feature extraction. Comparison experiments show that CCWT is better than frequently used extreme value and Hilbert–Huang transform methods. Then, Teager–Kaiser energy operator (TKEO) is applied to detect time-domain energy of fault signal envelop as fault feature. In addition to this, Hanning window is used to optimize TKEO to enhance fault feature and help with the accurate detection of demagnetization fault. Finally, motor prototype is manufactured for actual experiment and the results under different noise environments can certify the effectiveness and robustness of this proposed method.

Enhanced time-domain spreading is proposed for block-interleaved frequency division multiple access (B-IFDMA) with discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-s-OFDM). By repeating each consecutive modulation symbol prior to the spreading, we show that the DFT of the spreading sequence becomes a window function, which compared to the existing method of repeating the whole block of modulation symbols, offers a signal with both lower cubic metric (CM) and block error rate (BLER). Modulation symbol-specific spreading sequences are further shown to improve the BLER. The new transmission scheme is supported by both time- and frequency domain despreaders, as well as by two channel estimation methods for B-IFDMA.

The discrete Fourier transform (DFT) is carried out on a bounded time interval, which is equivalent to multiplying a signal under analysis by a rectangular window whose spectrum has the largest (among the other windows) side lobes. As a result, the effect called spectral leakage occurs. Multiplying the signal by the smoothing window reduces the splatter of its spectral components. There are several dozen variants of window functions as the DFT is used in a variety of problems. Of particular interest is the unique flat-top window, which is employed in broadband applications. In this study, we propose a new adjustable window with a quasi-rectangular spectrum and a method to reduce the level of the spectrum’s side lobes.

Waveform diversity, which can be used to obtain synthetic bandwidth or mitigate range ambiguity, interference, and folded clutters, has attracted a great deal of attention in recent years. However, the range sidelobe modulation effect between agile pulses yields high range-Doppler sidelobes in pulse-Doppler (PD) radar applications, because of which traditional window functions or mismatched filters (MMFs) do not apply. In this article, a Doppler-tuned matched filter is used to equivalently obtain the PD result. Then, to mitigate the high range-Doppler sidelobes, a two-dimensional MMF (2-D MMF) is proposed, and the relevant signal-to-noise ratio (SNR) loss is deduced. A cyclic algorithm is also designed to calculate the 2-D MMF for suppressing sidelobes over desired range-Doppler regions with constrained SNR loss and mainlobe width. Several simulations and an experiment based on real measured data of an airborne platform are conducted to illustrate the effectiveness of the proposed 2-D MMF.

It is well known that the nonlinear frequency modulation (NLFM) chirp waveform can shape advantageously the power spectrum density (PSD) such that the autocorrelation function exhibits reduced sidelobes as the window function. However, differences between the PSD and window function due to the Gibbs effects caused by the Fresnel integral would lead to deteriorative performance of the NLFM chirp waveform. In particular, the correlation function of NLFM waveform with Chebyshev PSD is seriously inconsistent with the lowest sidelobe level of the Chebyshev window function possesses. To overcome the inconsistency, therefore, in this letter, a novel NLFM waveform with modified Chebyshev window PSD is proposed, which combines the Chebyshev with edge distortion compensation, allowing, in theory, low sidelobe level as Chebyshev window. Using theoretical analysis also confirmed by simulation, this letter shows that the novel NLFM waveform possesses low sidelobes without high computational complexity in design.

A synthesis problem is solved for low-order windows with the sidelobe spectrum falloff rate equal to 12n decibel per octave (dB/oct), where n is an integer, that are optimal by the criterion of the minimum highest spectrum sidelobe level over a given frequency region outside the main lobe. To obtain this sidelobe falloff rate, it is proposed to synthesize the windows in the form of a portion of the Fourier series in terms of cosine functions with an odd number of half-waves along the observation interval. A synthesis method for the optimal functions with verification of the solution is developed. Order 3 to 6 windows with sidelobe falloff rates 12, 24, and 36 dB/oct are synthesized and their parameters are presented.

Spectral analysis is a significant technique applied in many fields to infer the signal spectral contents. However, the frequency resolution of a signal spectrum estimation result is limited by its finite data length, especially when using a Fourier-based method. Extra processing gain [i.e., signal-to-noise ratio (SNR) improvement] is always required for weak target detection. In this paper, a high-resolution spectrum estimation method using a deconvolution algorithm is proposed. According to classical spectral analysis, a power spectrum derived from a finite data length is related to the convolution of the true power spectrum from an infinite length data set with the power spectrum from a window function. Therefore, using a deconvolution algorithm on the power spectrum estimated by classical spectral analysis can remove the influence from the window function, such as spectral leakage. The deconvolved power spectrum can robustly obtain a sufficiently high-frequency resolution and low sidelobes with relatively few calculations. The proposed method can also provide a deconvolution gain, which plays an important role in weak signal detection as it is capable of enhancing the signal and reducing background noise. Its performance is analyzed in simulations as well as with measured experimental data.

Multistatic, radar-based, microwave breast cancer detection provides more information in a shorter period of time than the monostatic approach. However, artefact removal is harder in the multistatic case due to antenna coupling. In this study, a multi-step imaging system is proposed for the multistatic approach. The first step is responsible for artefact removal, and it includes signals grouping, windowing, filtering, and merging. The second step utilises combined doubled delay-multiply-and-sum beamforming, and produces the breast images. To test the proposed system, a heterogeneous breast phantom having two tumours was simulated and illuminated by ultra-wideband signals in multistatic scan. The simulation results show the success of the proposed system in both eliminating the artefact and clutter in the breast phantom image.

A robust low power Electrocardiogram (ECG) pre-processor is proposed to extract the useful information from biomedical signal. The methodology uses window-based efficient design that consumes less ...

Waveguide bends are key components of photonic integrated circuits, enabling complex layouts and high packing densities. Often waveguides at bends are wide and consequently multi-mode for lower loss propagation. Higher order modes, which are excited by the bend curvature, may degrade performance for devices downstream, such as extinction ratio in modulators. It is demonstrated that bend curvature functions inspired by window functions used in digital signal processing can greatly suppress the undesirable generation of higher order modes. The proposed curvature functions include sine to the power of $n$ , and Dolph-Chebyshev window. Coupled mode theory provides the insight that the suppression of higher order modes in a bend is related to the side-lobe suppression of the bend curvature Fourier transform. A particular application for the proposed bend geometries is mode division multiplexing, where inter-mode crosstalk may be significantly reduced.

In this work, we present a generalized formulation of the Slepian concentration problem on the sphere for finding band-limited functions with an optimal concentration in the spatial domain. By introducing weighting functions in the formulation of classical Slepian concentration problem and assigning different values to these weighting functions, we present two variants of the concentration problem namely the differential and the weighted Slepian concentration problem. In the differential Slepian concentration problem, we consider two regions on the sphere and find band-limited functions such that the energy is maximized in one region at the expense of the energy in the other region. We propose non-negative weighting using a spatial window function to formulate and solve the weighted Slepian concentration problem. Each problem can be solved by formulating it in the harmonic domain as an eigenvalue problem, the solution of which yields eigenfunctions that serve as alternative basis functions for the representation of band-limited signals and are referred to as Slepian functions. We also present and analyse the properties of the Slepian functions. To support the applications in acoustics and cosmology, we also provide a demonstration for the use of the proposed Slepian functions for the robust signal modeling and the estimation of the energy spectrum of red and white stochastic processes on the sphere.

Due to the epicyclic motion of planet gears, the vibration picked up from planetary gearboxes is different from that observed from the fixed-axis gearboxes. In particular, the vibration transfer path is time-varying, which makes the time synchronous averaging (TSA) not directly usable to reduce the nonsynchronous interferences for improving the signal-noise ratio (SNR) of vibration. Hence, it is difficult to detect teeth faults of planet and sun gears. In order to address this issue, a novel scheme is proposed in this paper, which combines the vibration separation, equi-angle resampling, and resonance demodulation approaches. In the proposed scheme, the complex envelope of the vibration is extracted by the fast kurtogram algorithm at first. Then, the envelope is equi-angle resampled to eliminate the inevitable speed fluctuations. Subsequently, a window function is used to grab the envelope data series at a fixed angular position related to the ring gear, such that the problems caused by time-varying vibration transfer paths are solved. Then, synthetic envelopes can be constructed by connecting the data in the data blocks according to the teeth mesh sequences of the interesting gear, where a data mapping scheme and a synthetic envelope determining strategy based on maximum kurtosis are introduced. Furthermore, the TSA is applied to the synthetic gear envelope to improve the SNR. Finally, spectral analysis is utilized to expose the characteristic frequencies. The effectiveness of the proposed method is validated by comparative experiments with the normal and faulty planet and sun gears in a planetary gearbox test rig.

In recent decades, with the rapid development of artificial intelligence technologies and bionic engineering, the spiking neural network (SNN), inspired by biological neural systems, has become one of the most promising research topics, enjoying numerous applications in various fields. Due to its complex structure, the simplification of SNN circuits requires serious consideration, along with their power consumption and space occupation. In this regard, the use of SSN circuits based on single-electron transistors (SETs) and modified memristor synapses is proposed herein. A prominent feature of SETs is Coulomb oscillation, which has characteristics similar to the pulses produced by spiking neurons. Here, a novel window function is used in the memristor model to improve the linearity of the memristor and solve the boundary and terminal lock problems. In addition, we modify the memristor synapse to achieve better weight control. Finally, to test the SNN constructed with SETs and memristor synapses, an associative memory learning process, including memory construction, loss, reconstruction, and change, is implemented in the circuit using the PSPICE simulator.

УДК 621.396.96 Предмет и цель работы: Анализ структуры выходного сигнала оптимального фильтра сжатия ЛЧМ-импульсов с целью выяснения причин несоответствия уровня боковых лепестков, получаемого при использовании стандартных сглаживающих окон, литературным данным. Методы и методология: Для расчета структуры отклика оптимального фильтра со сглаживающим окном общего вида используются стандартные методы математической физики и статистической теории обработки сигналов. Результаты: Приведены выражения для оценки максимального количества нулей и максимумов реакции оптимального фильтра сжатия ЛЧМ-импульсов, а также разноса между соседними и “одноименными” (с одинаковыми номерами) нулями и максимумами в зависимости от базы сигнала. Получены формулы для оценки потерь в отношении сигнал/шум из-за применения сглаживающих функций. Подробно рассмотрен случай применения оконных функций в виде набора косинусных гармоник ряда Фурье, которым описывается достаточно большое количество стандартных окон. Получено аналитическое выражение для выходного сигнала фильтра сжатия ЛЧМ-импульсов с использованием таких окон, приведена формула для оценки потерь в отношении сигнал/шум. Проведен сравнительный анализ эффективности применения окон Хэмминга и Блэкмана в зависимости от базы сигнала B. Показано, что при значениях B ≤ 80 более эффективным является использование окна Хэмминга. При больших значениях B более эффективным становится окно Блэкмана. С ростом B эффективность обоих окон возрастает, асимптотически приближаясь к приводимым в литературе показателям. Эмпирическим путем подобраны коэффициенты оконных функций, состоящих из трех косинусных гармоник ряда Фурье, что позволило уменьшить уровень боковых лепестков, по сравнению с применением окна Хэмминга, приблизительно на 0.34 дБ при B = 21 и на более чем 1 дБ при B = 7. Заключение: Полученные результаты позволяют сделать вывод, что при небольших базах сигнала задачу оптимизации параметров оконной функции нужно решать отдельно для каждого конкретного значения B . Добиться предельно низкого уровня боковых лепестков при этом, скорее всего, не удастся, но определенное улучшение характеристик фильтра сжатия ЛЧМ-импульсов вполне возможно. Ключевые слова: ЛЧМ-импульс, фильтр сжатия импульсов, оконная функция, уровень боковых лепестков Статья поступила в редакцию 11.09.2019 Radio phys. radio astron. 2019, 24(4): 300-313 СПИСОК ЛИТЕРАТУРЫ 1. Cook C. E. and Bernfeld M. Radar Signals : An Introduction to Theory and Application . New York, London: Academic Press, 1967. 550 p. 2. Barton D. K. Radar System Analysis and Modeling . Boston, London: Artech House Publishers, 2004. 566 p. 3. Ducoff M. R. and Tietjen B. W. Pulse Compression Radar. In: M. I. Skolnik, ed. Radar Handbook . New York, Chicago, San Francisco et al.: McGraw-Hill Companies, 2008. P. 8.1–8.44. 4. Levanon N. and Mozeson E. Radar Signals . Hoboken, New Jersey: John Wiley&Sons, Inc., 2004. 432 p. 5. Трухачев А. А. Радиолокационные сигналы и их применения . Москва: Воениздат, 2005. 320 с. 6. Кочемасов В. Н., Белов Л. А., Оконешников, В. С. Формирование сигналов с линейной частотной модуляцией . Москва: Радио и связь, 1983. 192 с. 7. Doerry A. W. Catalog of Window Taper Functions for Sidelobe Control . Technical Report SAND2017-4042, Sandia National Labs., Albuquerque, New Mexico and Livermore, California, USA, 2017. 208 p. DOI: 10.2172/1365510 URL: https://prod-ng.sandia.gov/techlib-noauth/access-control.cgi/2017/174042.pdf (дата обращения: 20.06.2019) 8. Heinzel G., Rudiger A. and Schilling R. Spectrum and spectral density estimation by the Discrete Fourier transform (DFT), including a comprehensive list of window functions and some new flat-top windows . Technical Report, Albert-Einstein-Institut, Hannover, Germany, 2002. 84 p. URL: https://pure.mpg.de/rest/items/item_152164_1/component/file_152163/content (дата обращения: 20.06.2019) 9. Дворкович В. П., Дворкович А. В. Оконные функции для гармонического анализа сигналов . Москва: Техносфера, 2016. 208 с. 10. Петьков А. А. Выбор рациональных вариантов весовых функций для цифровой фильтрации сигналов с линейной частотной модуляцией. 8-я Международная научная конференция по военно-техническим проблемам, проблемам обороны и безопасности, использованию технологий двойного применения “ MILEX INNOVATIONS -2019” Сборник научных статей, Часть 2 (16-17 мая 2019, Минск, Беларусь). Минск, Беларусь: “Лаборатория интеллекта”, 2019. С. 75–79. 11. Tiwari D . and Bhadauria S . S . Reduction in sidelobe and SNR improves by using Digital Pulse Compression Technique. Int. J. Adv. Res. Sci. Eng . 2017. Vol. 6, No. 7. P. 1056–1063. 12. Kowatsch M. and Stocker H. R. Effect of Fresnel ripples on sidelobe suppression in low time-bandwidth product linear FM pulse compression. IEE Proc. – F . 1982. Vol. 129, No. 1. P. 41–44. DOI: 10.1049/ip-f-1.1982.0007 13. Оконешников В. С., Кочемасов В. Н. Сжатие частотно-модулированных сигналов с небольшим произведением девиации частоты на длительность импульса. Зарубежная радиоэлектроника . 1987. № 1. С. 82–94. 14. Патент 20011125875 Российская Федерация, МПК G01S 13/00. Родионов В. В., Рукавишников В. М., Филонов Ю. В., Никитин Е. А., Шильман М. А., Чеснов В. Н., Белясов А. Н. 20.09.2001. 15. Мартыненко В. С. Операционное исчисление . Киев: Выща школа, 1990. 359 с. 16. Левин Б. Р. Теоретические основы статистической радиотехники . Книга 1 . Москва: Советское радио, 1969. 752 с. 17. Моисеев Н. Н., Иванилов Ю. П., Столярова Е. М. Методы оптимизации . Москва: Наука, 1978. 352 с. 18. Дегтярев Ю. М. Методы оптимизации . Москва: Советское радио, 1980. 272 с. 19. Reklaitis G. V., Ravindranand A., and Ragsdell K. M. Engineering Optimization . Methods and Applications . New Jersey: John Wiley & Sons, Inc., 1983. 684 p. 20. Tan Y. Particle Swarm Optimization Algorithms Inspired by Immunity-Clonal Mechanism and Their Applications to Spam Detection. Int. J. Swarm Intell. Res . 2010. Vol. 1, No. 1, P. 64–86. DOI: 10.4018/jsir.2010010104.

For numerous applications in the field of signal processing, it is desired to design a compact window that can simultaneously concentrate maximum energy in finite time interval and frequency band. Although zero-order discrete prolate spheroidal sequence (DPSS) meets this requirement, it is of infinite support. Limiting this sequence to finite support no longer guarantees the optimality property. This study aims at designing a discrete finite length window that can maximise the energy simultaneously in narrow time interval and frequency band. A multi-objective optimisation approach is adopted to obtain the upper bound of maximum achievable time and frequency domain energy concentrations for finite length sequences. The optimal sequence thus obtained is termed as the optimal window with finite support (OWFS), and its various associated properties are discussed. It is shown analytically that as the support of OWFS approaches infinity, it converges to zero-order DPSS. In order to illustrate its optimality, the compactness of the proposed OWFS is compared with those of various window functions. Extending the proposed OWFS, this study also discusses the formulation and associated properties of the zero-order periodic DPSS. Further, the closed form expression for the upper bound of achievable time and frequency domain energy concentrations is also derived.

The evaluation of pilots’ fatigue status is of substantial significance in aviation safety, which faces two major issues. They are how to get the fatigue status feature representation and how to identify the fatigue behavior status of pilots via electroencephalogram (EEG) signals. To solve the first issue, we propose a novel fatigue evaluation index via different window functions to compute the power spectrum of relative rhythms from EEG signals. Wavelet packet transform is used to decompose EEG signals from pilots to form four major rhythms, i.e., $\boldsymbol {\delta }$ wave, $\boldsymbol {\theta }$ wave, $\boldsymbol {\alpha }$ wave, and $\boldsymbol {\beta }$ wave, and the combined representation of their power spectrum curve area is the features of pilots’ mental status. To solve the second issue, we propose a new deep contractive autoencoder (AE) network with a softmax (SM) classifier to detect the multistatuses of mental fatigue workload. The recognition results of our model are also compared with that of other models such as the deep AE network with a SM classifier model. The experimental results show that our deep learning model has superior classification performance, and the recognition accuracy of fatigue mental status is up to 91.67%, which shows that the proposed method performs excellently compared with the state-of-the-art methods.

A fixed window function which is similar in shape to a semi-ellipse is proposed. The semi–ellipse which has its major axis to be equal to the window length and the minor axis at unity produced about 4.2 dB lower ripple ratio than the rectangular window. The proposed window function is derived from the equation of an ellipse in the explicit and parametric forms. First of all, the spectral characteristic of the proposed window is studied in terms of spectral parameters and compared with other fixed windows like Rectangular, Bartlett, Hann, Hamming and Blackman windows. The window simulation results reveal that the proposed window produced comparable spectral characteristic with existing standard fixed windows. Secondly, the paper presents the application of the proposed window in a digital filter design. The filter analysis comparison results with other fixed windows namely Bartlett, Von Hann, Hamming, and Kaiser window, an adjustable window, confirm that filter design with the proposed window exhibits good spectral characteristic, and can be used to design better filter than the Bartlett window using less than half the Bartlett’s filter length for a fixed transition width. The similicity of its coefficients formulation and design algorithm makes it a good choice for digital filter design applications.

In synthetic aperture radar (SAR) imaging, geometric resolution, sidelobe level (SLL) and signal-to-noise ratio (SNR) are the most important parameters for measuring the SAR image quality. The staring spotlight mode continuously transmits signals to a fixed area by steering the azimuth beam to acquire azimuth high geometric resolution, and its two-dimensional (2D) impulse response with the low SLL is usually obtained from the 2D weighted power spectral density (PSD) by the selected weighting window function. However, this results in the SNR reduction due to 2D amplitude window weighting. In this paper, the staring spotlight SAR with nonlinear frequency modulation (NLFM) signal and azimuth non-uniform sampling (ANUS) is proposed to obtain high geometric resolution SAR images with the low SLL and almost without any SNR reduction. The NLFM signal obtains non-equal interval frequency sampling points under uniform time sampling by adjusting the instantaneous chirp rate. Its corresponding PSD is similar to the weighting window function, and its pulse compression result without amplitude window weighting has low sidelobes. To obtain a similar Doppler frequency distribution for low sidelobe imaging in azimuth, the received SAR echoes are designed to be non-uniformly sampled in azimuth, in which the sampling sequence is dense in middle and sparse in both ends, and azimuth compression result with window weighting would also have low sidelobes. According to the echo model of the proposed imaging mode, both the back projection algorithm (BPA) and range migration algorithm (RMA) are modified and presented to handle the raw data of the proposed imaging mode. Both imaging results on simulated targets and experimental real SAR data processing results of a ground-based radar validate the proposed low sidelobe imaging mode.

Wireless communications became an integrated part of the human life. Fifth generation (5G) is the modern communication which provides enhanced mobile broadband (eMBB), ultra reliable low latency communications (URLLC), and massive machine type communication (mMTC). Thus, 5G have to provide coverage to multi-numerology devices, therefore, modulation and access schemes are suggested in the literature such as cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) and filtered OFDM (f-OFDM). CP-OFDM suffers from the high out of band emission which limited the multi-numerology applications. In f-OFDM, the out of band emission can be suppressed to an accepted extent such that different numerologies can be coexisting. On the other hand, f-OFDM can be more improved by using a proper filtering approach. In this paper three different filters are suggested based windowed-sinc function; Hanning, Hamming, and Blackman. Simulation results show that the proposed filters are promising for high spectral efficiency and out of band emission rejection. Furthermore, the bit error rate, error vector magnitude, and power spectral density are further improved with respect to CP-OFDM scheme but some trade-off is present. Overall, the suggested windowed-sinc filters are outperforming the traditional CP-OFDM. As a conclusion, the suggested windnowed-sinc filters have no limitations on the modulation order or the number of subcarriers utilized in the system.

Recently, we proposed a Spectral Domain Sparse Representation (SDSR) approach for the direction-of-arrival estimation of signals incident to an antenna array. In the approach, sparse representation is applied to the conventional Bartlett spectra obtained from snapshots of the signals received by the antenna array to increase the direction-of-arrival (DOA) estimation resolution and accuracy. The conventional Bartlett spectra has limited dynamic range, meaning that one may not be able to identify the presence of weak signals in the presence of strong signals. This is because, in the conventional Bartlett spectra, uniform weighting (window) is applied to signals received by various antenna elements. Apodization can be used in the generation of Bartlett spectra to increase the dynamic range of the spectra. In Apodization, more than one window function is used to generate different portions of the spectra. In this paper, we extend the SDSR approach to include Bartlett spectra obtained with Apodization and to evaluate the performance of the extended SDSR approach. We compare its performance with a two-step SDSR approach and with an approach where Bartlett spectra is obtained using a low sidelobe window function. We show that an Apodization Bartlett-based SDSR approach leads to better performance with just single-step processing.

Passive Intermodulation (PIM) distortion is a major problem in wireless communications which limits cell coverage and data rates. Passive nonlinearities result in weak intermodulation (IMD) products that are very difficult to diagnose, troubleshoot and model. To predict PIM, behavioral models are used where spectral components of PIM are estimated from the power spectral density at the output of the model. The primary goal of this paper is to study the effect of window functions on the capability of the power spectral density computed from the periodogram of signal realizations to predict low power PIM components in a wideband multichannel communication system. Different window functions are analyzed and it is shown that windows with high side-lobe level fail to predict PIM components which are close to the main channels due to their high spectral leakage, while window functions with low roll-off rate of the side lobes fail to predict low power higher order PIM components especially when the frequency separation between the main carriers is high. These results are supported by simulations of the power spectral density computed using signal realizations of an LTE carrier aggregated system.

This article introduces an improved Gerchberg–Papoulis algorithm (IGPA) to resolve truncation errors in planar near-field (NF) antenna measurement and seeks to define the most accurate means of recovering patterns. The truncation errors in planar NF measurements can be reduced by considering the evanescent modes and introducing a new convergence criterion and a window function in the IGPA. A detailed design procedure is presented, and its effect on the field distribution of key parameters is discussed, which can be found in the Appendix at https://web.xidian.edu.cn/xli/files/Appendix.pdf . The results of a simulation and physical measurement are used to assess the validity and applicability of the proposed approach.

A new window function is proposed in this Letter, which can be used for two different applications like, suppression of co-channel interference and suppression of harmonics, by just varying the two parameters in the window. The proposed window is compared with the other efficient windows employed in these applications, and it is found to be equally or more efficient.

Memory-resistor (Memristor) has drawn considerable attention of the researchers in the last decade due to its remarkable properties. After the first concept of memristor, proposed by Leon Chua in 1...