Anti-aliasing Filter Research Articles

An efficient low-delay polyphase implementation method for active noise control systems

When implementing active noise control systems on signal processing hardware, the time delay introduced by electronic components (especially components requiring additional lowpass filters or introducing fixed-sample-size delays) may adversely affect the noise control performance. One common approach to reducing this delay is to use a high sampling rate, but this increases the computation significantly when implementing the ANC filters in real time. In the current work, a polyphase-structure-based filter design method is developed for active noise control systems that can reduce the computation load for real-time filter implementation but do not introduce an additional time delay. Although the computation reduction capability of a polyphase filter structure is well known for multi-rate systems, the traditional use of such multi-rate systems requires additional anti-aliasing and reconstruction filters which introduces an additional time delay. Thus, in delay-sensitive applications, such as active noise control, this method was previously applied only on the filter adaption phase, instead of directly on the real-time filtering process. In this article, a filter decomposition method using the minimum-phase technique is proposed to decompose an ANC filter into two multiplicative causal filters both of which have lowpass frequency response shapes at high frequencies such that the polyphase structure can be applied directly to the two multiplicative causal control filters without introducing additional anti-aliasing and reconstruction filters. Results show that, compared with various traditional low sampling rate implementations, the proposed method can significantly improve the noise control performance. Compared with the non-polyphase high-sampling rate method, the real-time computations that increase with the sampling rate are improved from quadratically to linearly.

Design of Digital Lock-in Amplifier based on FPGA

Abstract In order to achieve high-precision measurement of strong noise background signal, a digital lock-in amplifier based on field programmable gate array (FPGA) is designed. The core of the lock-in amplifier consists of a signal processing module, an acquisition and quantisation module and a digital demodulation module. The signal processing module completes the amplification and gain adjustment of the input signal and modulates the signal to be measured into a specific frequency band, which is digitally quantised by the analog to digital converter (ADC) after anti-aliasing filtering and transmitted to the FPGA, and the signal to be measured is extracted by phase-sensitive detection through the mutual-correlation digital demodulation method, thus realising the detection of the weak signal. The performance of the lock-in amplifier is evaluated with a signal generator as the input source, and the results show that the signal-to-noise improvement ratio is 35dB and the relative measurement error of voltage is less than 0.03% after the digital lock-in amplifier is processed, which accurately restores the direct current (DC) signals in the noisy background, and provides an effective technical way for the accurate measurement of weak signals.

Dynamic Matching of Reconstruction and Anti-Aliasing Filters in Adaptive Active Noise Control

Constrained by the computing power, adaptive active noise control systems often have a low sampling rate. Therefore, reconstruction filters and anti-aliasing filters with fixed parameters are generally adopted to eliminate the mirror noise and aliasing noise, respectively; however, they may boost the group delay of the system. A dynamic matching method based on dual sampling rates is proposed to dynamically adjust the parameters of the reconstruction and anti-aliasing filters, according to the characteristics of the primary sound source, for a compromise between high-frequency noise and group delay. In digital high-sampling-rate regions, data that include high-frequency information are analyzed regularly, following which the parameters of the reconstruction filters and those of the anti-aliasing filters are dynamically matched. In digital low-sampling-rate regions, the estimation of the secondary path transfer function is updated. The results of laboratory experiments show that the proposed method not only can suppress the mirror and aliasing noise for primary sound sources with different spectra, but can also effectively reduce the group delay and improve the noise reduction performance of a system.

Fully real-time configurable analogue implementation of continuous-time transfer function: Application on fractional controller

This paper proposes a new electronic analog circuit to realize real-time fully configurable continuous-time transfer function. The proposed circuit serves various purposes, including smart controllers, fractional-order controllers, optimal controllers, anti-aliasing filter, and programmable filters. The input signal of the transfer function is continuous and remains continuous throughout the circuit until the output signal is obtained. The proposed approach decomposes the transfer function into elementary first and/or second-order low-pass filters. A new analog first-order low-pass filter circuit is presented, offering advantages over conventional active first-order low-pass filters circuits. These benefits include DC gain and time constant independent of resistor ohmic values, enabling the use of smaller resistors and capacitors for low frequencies, and an expanded frequency working range. Similarly, a new analog circuit for a second-order low-pass filter is proposed, specifically used to obtain complex conjugate poles. The use of digital potentiometers and digital switches controlled by a micro-controller, makes this analog circuit configurable in real-time. As an application, the new circuit is used to realize fractional integrator controller. The circuit gives good similarity between theoretical and experimental measurements.

Making Phase-Picking Neural Networks More Consistent and Interpretable

Abstract Improving the interpretability of phase-picking neural networks remains an important task to facilitate their deployment to routine, real-time seismic monitoring. The popular phase-picking neural networks published in the literature lack interpretability because their output prediction scores do not necessarily correspond with the reliability of phase picks and can even be highly inconsistent depending on how we window the waveform data. Here, we show that systematically shifting the waveforms during training and using an antialiasing filter within the neural network architecture can substantially improve the consistency of the output prediction scores and can even make them scale with the signal-to-noise ratios of the waveforms. We demonstrate the improvements by applying these approaches to a commonly used phase-picking neural network architecture and using waveform data from the 2019 Ridgecrest earthquake sequence.

Dynamic Range of a Digital Radio Receiver with a Photonic Analog-to-Digital Converter

The article is devoted to determining the requirements for the preliminary, analog part of the receiver and its structure when using a photonic ADC. The subject of research in this case is the issues of ensuring a large dynamic range of signals at the input of a receiver with a photonic ADC. The parameters and properties of the PADC with optical quantization and discretization are investigated. The distinctive features of the PADC are a high sampling rate, about 100 GHz, the possibility of increasing the carrier-to-noise ratio (CNR) and the effective number of bits (ENOB) due to the amplification of the carrier or modulating signal, and a low noise factor of microwave photonic elements. The presented advantages make it possible to reduce the structure of the analog part of the receiver by eliminating the mixer and anti-aliasing filter, as well as to achieve better sensitivity due to a lower level of internal noise. The study also revealed a limitation of the dynamic range imposed by the photonic element base. The reason for the limitation is the nonlinearity of the electro-optical modulators used and the limitation of the upper limit of the dynamic range to the photodetectors used. All this leads to requirements under which the analog part must provide significant amplification of the received radio signal, as well as the implementation of a variable gain. As a result, structural solutions are presented in the form of multichannel switching circuits. The principle of operation lies in the fact that each channel, consisting of a cascade of linear amplifiers and a PADC, has a different gain, and in the digital processing unit, channels are compared and switched depending on the signal level. At the same time, the level should be in the 'corridor' of acceptable values for the application of the PADC and within the dynamic range. The presented structural solutions will make it possible to implement radio receivers capable of receiving and processing a microwave signal without transferring the signal to an intermediate frequency. At the same time, the required signal amplification level of 105 - 106 can be achieved, which makes it possible to achieve a signal level of 2.5-9.5 V, at which the photonic analog-to-digital converter has the best CNR and ENOB indicators.

Modified instantaneous power theory control of dynamic voltage restorer powered by photovoltaic system

<span lang="EN-US">Power quality issues have become widespread due to nonlinear electronic converters and loads. Nonlinear components in the power system hamper the power quality, network efficiency and voltage regulation. The power quality issues like sag, swell, and voltage unbalance can be reduced by employing a dynamic voltage restorer (DVR). DVR provides the compensating power from a DC source to minimize the effect of sag, swell, and voltage unbalance. This article presents a power system with DVR using a photovoltaic system (PV) as a DC source instead of a conventional battery source. This article proposes a modified instantaneous power (PQ) control technique to generate the reference signal of load voltage to assure the DVR's superior performance. This modified technique uses an anti-aliasing filter to generate a reference signal. This proposed technique is tested under extreme power quality issues of 80% sag, 20% sag, 120% swell, 170% swell, and voltage unbalance. The DVR is modeled and simulated using MATLAB/Simulink. A comparison is made between the traditional and modified PQ methods from the obtained results. The analyzed results under severe power quality issues suggest that the proposed P-Q control technique is a preferable option for the DVR with PV as a DC power supply.</span>

A 600 MHz-BW 154.3 dB-FoM current-mode continuous-time pipelined ADC in 12 nm CMOS

A current-mode two-stage continuous-time pipelined (CTP) ADC for wideband receivers is proposed in this paper, to eliminate power-hungry front-end trans-impedance amplifier (TIA). An improved current mirror with low input impedance and high linearity is used to receive the current input signal and duplicate it to the delay chain and the quantization path of the 3-bit first stage. Then, the residue current is amplified and filtered by an embedded 1st-order TIA and further quantized by the second stage, which is implemented by a VCO-based quantizer to improve ADC energy efficiency and anti-aliasing filtering. Simulation results in a 12 nm FinFET process show that clocked at 4.8 GS/s, the proposed ADC achieves 55.7 dB SNDR for a 600 MHz bandwidth and consumes only 83.4 mW power under supplies of 0.9 V, 1.2 V, and 1.5 V, corresponding to an excellent FoM of 154.3 dB.

Detection of Epilepsy patients using coot optimization based feed forward multilayer neural network

ABSTRACT A familiar nervous system disorder characterised by seizures is called as Epilepsy. It is indeed hard to control the suitable type as an outcome of insufficient EEG information. In order to overcome these issues, a Multilayer Neural Network (MLNN)-based classifier is proposed to recognise if the patients are affected by epileptic disease or not. EEG signal is a contribution, and the input signal is preprocessed using antialiasing filter, finite impulse response, and band pass filter to eradicate unwanted noise present in the signal. After preprocessing, the features extracting process is done, and four extraction techniques are proposed in order to calculate the feature coefficient. The feature extraction outcome is fed into the MLNN classifier to predict the disease. MLNN performs with Coot-Optimization to reduce error and increase prediction accuracy. The future ideal applied in Matlab-software carried out numerous act metrics, and these parameters attained better performance such as accuracy of 96.5%, error of 0.03, precision of 98%, specificity is 97%, sensitivity is 95%, and so on. This displays the effectiveness of the future ideal than existing approaches such as ANN, SVM, KNN and NB. Based on this proposed classification, the epileptic disease prediction can be improved on this technique and can provide a living standard for patients.

Capacitor Condition Monitoring Method for Low-Capacitance StatComs: An Online Approach Using the Inherent Second-Harmonic Oscillations

The cascaded H-bridge low-capacitance static compensator (LC-StatCom) deliberately reduces the capacitor size while allowing large oscillations in capacitor voltages. When a capacitor deteriorates, its capacitance decreases or/and its equivalent series resistance (ESR) increases, compromising StatCom performance and safety. For this reason, the condition monitoring of the capacitors is important to schedule maintenance before failure. This letter introduces a cost-effective and nonintrusive method to monitor the condition of capacitors online. The proposed method offers real-time monitoring without requiring additional hardware or signal injection. The method uses averaged low-frequency signals instead of instantaneous high-frequency signals that can be corrupted by undesired high-frequency noise. Specifically, the method takes advantage of the inherent twice-fundamental-frequency oscillations on the capacitor voltage and current to identify the ESR and capacitance values. The method takes into account the influence of antialiasing filters required for sampling process. The letter shows experimental results that validate the fast and accurate performance of the proposed capacitor condition monitoring.

A test for the absence of aliasing or white noise in two-dimensional locally stationary wavelet processes

Either intentionally or unintentionally, sub-sampling is a common occurrence in image processing and can lead to aliasing if the highest frequency in the underlying process is higher than the Nyquist frequency. Several techniques have already been suggest in order to prevent aliasing from occurring (for example applying anti-aliasing filters), however there is little work describing methods to detect for it. Recently, Eckley and Nason (Biometrika 105(4), 833–848, 2018) developed a test for the absence of aliasing and/or white noise in locally stationary wavelet processes. Following Eckley and Nason (Biometrika 105(4), 833–848, 2018), we derive the corresponding theoretical consequences of sub-sampling a two-dimensional locally stationary wavelet process and develop a procedure to test for the absence of aliasing and/or white noise confounding at a fixed point, demonstrating its effectiveness and use through appropriate simulation studies and an example. In addition, we outline some possibilities for extending these methods further, from images to videos.

A Digital Frequency-Dependent I/Q Imbalance and Group Delay Estimation and Compensation Modules for mmWave Single Carrier Baseband Transceivers

This paper proposes the estimation and compensation modules of digital frequency-dependent (FD) I/Q imbalance and group delay for single carrier (SC) mode with 15 Gbps throughput rate in the millimeter-wave (mmWave) band. The proposed compensation module of a digital recursive filter can mitigate FD I/Q imbalance effects caused by the -3 dB corner imbalance of the reconstruction and anti-aliasing filters of I/Q branches. The proposed recursive filter with the appropriate initial coefficients based on the result of Golay sequence estimation can shorten the convergence time and precisely acquire the desired coefficients. The average image rejection ratio (IRR) performance after compensating by the proposed module can be improved from 21.97 dB to 47.54 dB. Besides, the group delay distortion in reconstruction and anti-aliasing filters will cause intersymbol interference to distort the in-band signal. We employ a digital equalization filter with the filter coefficients derived from the correlation results based on the Golay sequence to compensate the in-band group delay distortion. After the proposed group delay is pre-compensation at TX, the system-level performance of error vector magnitude (EVM) performance is improved by 6.21 dB to -27.78 dB to satisfy the IEEE 802.11ad/ay requirement in 64-QAM mode. The inner RX BER performance with the FD I/Q imbalance and the group delay compensation modules can achieve 3 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> at 23 dB and also satisfy the system requirement at SNR of required 25.52 dB. A four-times parallelism architecture is proposed to work at a clock rate of 625 MHz with 64-QAM mode. The gate count and power consumption of the proposed design are 154.4 K and 16.2 mW, respectively.

Spatial aliasing quantification and sampling frequency selection in imaging sensors.

Sampling, whether it be spatial or temporal, is a common occurrence. A result of this fact is the need for an anti-aliasing filter, which effectively limits high frequencies and prevents them from folding over and appearing as a low(er) frequency when sampled. In typical imaging sensors, such as optics plus focal plane detector(s), the optical transfer function (OTF) acts as a spatial anti-aliasing filter. However, decreasing this anti-aliasing cutoff frequency (or lowering the curve in general) via the OTF is tantamount to image degradation. On the other hand, the lack of high-frequency attenuation produces aliasing within the image, which is another form of image degradation. In this work, aliasing is quantified, and a method for sampling frequency selection is brought forth.

Impact of resampling interpolation FIR filter in the practical Kramers-Kronig receiver.

The practical Kramers-Kronig (KK) receiver has been a competitive receiving technique in the data-center, medium reach, and even long-haul metropolitan networks. Nevertheless, an extra digital resampling operation is required at both ends of the KK field reconstruction algorithm due to the spectrum broadening caused by adopting the nonlinear function. Generally, the digital resampling function can be implemented by using linear interpolation (LI-ITP), the Lagrange cubic interpolation (LC-ITP), the spline cubic interpolation (SC-ITP), time-domain anti-aliasing finite impulse response (FIR) filter method (TD-FRM) scheme, and fast Fourier transform (FFT)-based scheme. However, the performance and the computational complexity analysis of different resampling interpolation schemes in the KK receiver have not been thoroughly investigated yet. Different from the interpolation schemes of conventional coherent detection, the interpolation function of the KK system is followed by the nonlinear operation, which will broaden the spectrum significantly. Due to the frequency-domain transfer function of different interpolation schemes, the broadened spectrum will have a potential spectrum aliasing, which will cause serious inter-symbol interference (ISI) and further impair the KK phase retrieval performance. We experimentally investigate the performance of different interpolation schemes under different digital up-sampling rates (i.e. the computational complexity) as well as the cut-off frequency, the tap number of the anti-aliasing filter, and the shape factor of the TD-FRM scheme in a 112-Gbit/s SSB DD 16-QAM system over 1920-km Raman amplification (RFA)-based standard single-mode fiber (SSMF). The experimental results involve that the TD-FRM scheme outperforms other interpolation schemes and the complexity is reduced by at least 49.6%. In fiber transmission results, take 20% soft decision-forward error correction (SD-FEC) of 2×10-2 as the threshold, the LI-ITP and LC-ITP schemes only reach 720-km while others can reach up to 1440-km.

Measurement and Control System for Atomic Force Microscope Based on Quartz Tuning Fork Self-Induction Probe.

In this paper, we introduce a low-cost, expansible, and compatible measurement and control system for atomic force microscopes (AFM) based on a quartz tuning fork (QTF) self-sensing probe and frequency modulation, which is mainly composed of an embedded control system and a probe system. The embedded control system is based on a dual-core OMAPL138 microprocessor (DSP + ARM) equipped with 16 channels of a 16-bit high-precision general analog-to-digital converter (ADC) and a 16-bit high-precision general digital-to-analog converter (DAC), six channels of an analog-to-digital converter with a second-order anti-aliasing filter, four channels of a direct digital frequency synthesizer (DDS), a digital input and output (DIO) interface, and other peripherals. The uniqueness of the system hardware lies in the design of a high-precision and low-noise digital-analog hybrid lock-in amplifier (LIA), which is used to detect and track the frequency and phase of the QTF probe response signal. In terms of the system software, a software difference frequency detection method based on a digital signal processor (DSP) is implemented to detect the frequency change caused by the force gradient between the tip and the sample, and the relative error of frequency measurement is less than 3%. For the probe system, a self-sensing probe controller, including an automatic gain control (AGC) self-excitation circuit, is designed for a homemade balanced QTF self-sensing probe with a high quality factor (Q value) in an atmospheric environment. We measured the quality factor (Q value) of the balanced QTF self-sensing probes with different lengths of tungsten tips and successfully realized AFM topography imaging with a tungsten-tip QTF probe 3 mm in length. The results show that the QTF-based self-sensing probe and the developed AFM measurement and control system can obtain high quality surface topography scanning images in an atmospheric environment.

FPGA-Based Smart Sensor to Detect Current Transformer Saturation during Inrush Current Measurement

Current transformer saturation affects measurement accuracy and, consequently, protection reliability. One important concern in the case of overcurrent protections is the discrimination between faults and inrush current in power transformers. This paper presents an FPGA-based smart sensor to detect current transformer saturation, especially during inrush current conditions. Several methods have been proposed in the literature, but some are unsuitable for inrush currents due to their particular waveform. The proposed algorithm implemented on the smart sensor uses two time-domain features of the measured secondary current: the second-order difference function and the third-order statistic central moment. The proposed smart sensor presents high effectiveness and immunity against noise with accurate results in different conditions: different residual flux, resistive burdens, sampling frequency, and noise levels. The points at which saturation starts are detected with an accuracy of approximately 100%. Regarding the end of saturation, the proposed method detects the right ending points with a maximum error of a sample. The smart sensor has been tested on experimental online and real-time conditions (including an anti-aliasing filter) with accurate results. Unlike most existing methods, the proposed smart sensor operates efficiently during inrush conditions. The smart sensor presents high-speed processing despite its simplicity and low computational cost.

A2FWPO: Anti-aliasing filter based on whale parameter optimization method for feature extraction and recognition of dance motor imagery EEG

The classification accuracy of EEG signals based on traditional machine learning methods is low. Therefore, this paper proposes a new model for the feature extraction and recognition of dance motor imagery EEG, which makes full use of the advantage of anti-aliasing filter based on whale parameter optimization method. The anti-aliasing filter is used for preprocessing, and the filtered signal is extracted by two-dimensional empirical wavelet transform. The extracted feature is input to the robust support matrix machine to complete pattern recognition. In pattern recognition process, an improved whale algorithm is used to dynamically adjust the optimal parameters of individual subjects. Experiments are carried out on two public data sets to verify that anti-aliasing filter-based preprocessing can improve signal feature discrimination. The improved whale algorithm can find the optimal parameters of robust support matrix machine classification for individuals. This presented method can improve the recognition rate of dance motion image. Compared with other advanced methods, the proposed method requires less samples and computing resources, and it is suitable for the practical application of brain-computer interface.

Методика расчета параметров антиалайсинговых фильтров для коррекции спектральных характеристик в зависимости от используемых структур дискретизации массива светофильтров

When developing algorithms and methods for generating and processing image signals (IS) used in devices based on single-matrix light-to-signal converters (LSC), the effects of not only the elements of the system included in the optical pathway (OP) located directly between the exposed image and device sensor, but also the specifics of the structure of color filter arrays (CFA) used in such cameras, applied to the surface of the matrix. In this article analyzed the most popular SSF subsampling structures and their impact on the spatial characteristics of the generated images. Based on the model for constructing these characteristics, a method is given for calculating the optimal parameters of anti-aliasing filters that match the properties of the OP and the sensor for a given characteristic of the optical system. Specific examples of calculating and optimizing such filters and evaluating their impact on the amplitude characteristics of signals are given. Based on the results of applying the developed method, formulated recommendations for the design of the CFA.

Design and Implementation of Output Circuitry for Millimeter-wave Direct Detection Radiometer

This paper presents a design and an implementation of an output circuitry for a millimeter-wave direct detection radiometer. This circuitry is based on commercially available ultra-low-noise op-amp and consist of an active anti-aliasing filter and DC amplifier. The prototype of this circuitry has been realized and evaluated.

Precision Feedback Control Design of Miniature Microwave Discharge Ion Thruster for Space Gravitational Wave Detection

The space gravitational wave detection mission has put forward multiple performance requirements for micro-newton thrusters, such as “fast response, high resolution, and low noise”. In order to solve the problem that the traditional open-loop propulsion system can hardly meet the high-precision performance, the microwave ion thruster with high accuracy and controllability of thrust estimation is adopted as the research object, and the precision feedback control method combining analog circuit and digital control technology is adopted to achieve a resolution of less than 0.1 μN, fast response of 20 ms, and 10−3~1 Hz frequency band noise less than 0.05 μN/Hz1/2 of the thrust performance. Experimental results show that, compared with open-loop regulation, the feedback control can effectively suppress various noises and disturbances caused by device temperature drift and complex operating characteristics of the thruster, and the anti-aliasing filter scheme adopted in this paper can suppress the folding of high-frequency data in the low- and medium-frequency bands during the digital control process, while it can effectively improve the system performance and reduce the impact of thrust noise. The feedback control strategy proposed in this paper verifies the possibility of a microwave ion thruster as an actuator for super “static and precise” space experiment satellites and provides a feasible solution for the application of a microwave ion thruster in deep space science experiment missions such as gravitational wave detection.