Finite Impulse Response Band-pass Filter Research Articles

A 16-bit 18-MSPS flash-assisted SAR ADC with hybrid synchronous and asynchronous control logic

This paper presents a 16-bit, 18-MSPS (million samples per second) flash-assisted successive-approximation-register (SAR) analog-to-digital converter (ADC) utilizing hybrid synchronous and asynchronous (HYSAS) timing control logic based on an on-chip delay-locked loop (DLL). The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter (CDAC) than the synchronous and asynchronous SAR ADC. Therefore, the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent. In addition, the foreground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter (FIR-BPF) based least-mean-square (LMS) algorithm in an off-chip FPGA (field programmable gate array). Fabricated in 40-nm CMOS process, the prototype ADC achieves 94.02-dB spurious-free dynamic range (SFDR), and 75.98-dB signal-to-noise-and-distortion ratio (SNDR) for a 2.88-MHz input under 18-MSPS sampling rate.

Phase analysis of signals using frequency-dependent attenuation for measurements of seismic waves

Attenuation refers to any decrease in the power of a propagated signal through a medium. Attenuation measurement techniques include ultrasonic, resonance bar, and stress-strain methods. The stress-strain method measures elastic and viscoelastic properties in the seismic frequency range. The signals received via attenuation measurement systems using the stress-strain method can be considerably weak. Moreover, the noise in these signals causes errors when estimating the signal phase-angle difference between the sample signal and probe signal, thereby reducing system precision and measurement accuracy. Accurate measurements of such phase differences are essential to the measurement of attenuation. A seismic-wave attenuation with frequency-dependent measurement based on the stress-strain method and digital signal processing techniques has been performed. The system estimates the attenuation of a rock by measuring the phase shift in the stress-strain cycle. As a preprocessing method, the finite impulse response band-pass filters are designed to eliminate the influence of noise and direct current offset while ensuring that the phase difference of the measured signal remains unchanged. Three methods for phase difference estimation, i.e., crosscorrelation, fast Fourier transform (FFT), and Hilbert transform are compared, for different signal-to-noise ratios, sampling frequencies, data sample lengths, and true phase differences. The results find that the phase difference estimation based on FFT is the best among all three methods and can effectively improve the precision of the experimental results. Simulation and measurement results further indicate that the attenuation measurement system achieves stable and reliable attenuation measurements in the range of 3–2000 Hz.

FIR digital filter design based on improved artificial bee colony algorithm

The traditional swarm intelligence optimization algorithm is prone to fall into local optimal solutions in finite impulse response (FIR) digital filter design and has slow convergence speed. In order to optimize the design of FIR filter, a FIR digital filter design method based on improved bee colony (ABC) algorithm is proposed. This improved ABC algorithm can adaptively adjust the step size of the selected neighborhood of nectar source location. At the same time, the information of the global optimal solution is used to guide the search of candidate solution, which improves the global search ability of the algorithm. The improved ABC algorithm can balance the conflict between local search ability and global search ability, so it can achieve better optimization effect. The time and space complexity of the algorithm is analyzed in detail. Then, the improved ABC algorithm is used to design three typical FIR digital filters, namely low-pass, band-pass and band-stop filter. The performance of the designed filter is tested by simulation experiments. The experimental results show that compared with other state-of-the-art optimization algorithms, the proposed FIR filter design method has achieved better effect and performance. Meanwhile, the proposed design method has shorter optimization time. The superiority of the proposed method is verified.

FPGA Design of a High- Resolution FIR Band-Pass Filter by Using LabVIEW Environment

Designers regularly use Finite Impulse Response (FIR) filters to fulfil the need for current electronic design applications such as signal or image processing and digital communications because of the remarkable selectivity computational efficiency. Fast and efficient information processing requires a dedicated microprocessor or a digital signal processor that may not always be available or provide enough performance. In such scenarios, designers can configure FPGAs for processing digitized signals. One of the most popular signal processing applications is filtering. Unlike the Infinite Impulse Response (IIR) filters, FIR filters do not have analog equivalent circuits. For this purpose, continuous time-discrete time conversion is not possible with the help of transforms. Because analog filters cannot have a finite impulse response, the design methods of FIR filters can be made as windowing method, pulse response truncation, and optimal filter design method. Considering this information, it aims to digitally separate two signals with different frequencies (2.4 kHz and 4.2 kHz), which are given to the input as analog, to obtain the desired information signal and suppress other signals. We preferred to use LabVIEW graphical programming language to get the digital FIR filter coefficients. We selected rectangular windowing, set the digital filter's sampling frequency as 18720 Hz, and determined the filter's coefficient with high-frequency resolution as 24. Using filter coefficients in the real-time FPGA-VHDL environment, we showed the performance and resource consumption. LabVIEW is used for simulation as well as obtaining filter coefficients. In addition, we compared both simulation and real-time FPGA-VHDL application output waveforms and examined both platforms' advantages and disadvantages.

DFIG-based Wind Energy Conversion System Using Matrix Converter Under Unbalanced and Harmonic Grid Conditions with Band Pass-FIR Filters

This paper presents a modest control strategy of a doubly fed induction generator (DFIG)-based wind electric conversion system (WECS) with matrix converter, under unbalanced and harmonic grid conditions. Tedious sequence decomposition process and complex control reference calculations are avoided in the proposed control methodology. To obtain power grid-friendly operation, Band Pass-finite impulse response (BP-FIR) filters are designed to achieve four different control targets: sinusoidal stator current, sinusoidal rotor current, smooth stator real and reactive power and constant electromagnetic torque. In addition to active power reference from Maximum Power Point Tracking (MPPT) controller and desired reactive power reference, BP-FIR filters are used to synthesize space vectors of direct matrix converter. The effectiveness of the proposed approach is tested for a wide range of wind speeds.

Sharp transition FIR bandpass filter for processing bioelectric signals

The main objective in a filter module is to improve the signal-to-noise (SNR) ratio, intelligently extract certain frequency components or separation of frequency bands among other applications. These much needed filters can help in areas of speech or biomedical signal processing. A sharp transition (ST) finite impulse response (FIR) band pass filter (BPF) is proposed for any filter order (N). The FIR filter is implemented with least passband ripple and a satisfactory stopband attenuation. The proposed filter design permits to set the fiduciary edges for any filter order. The merits of this proposed ST FIR filter includes its linearity, sharpness of the transition band and mitigating the effects of the Gibb’s phenomenon at the fiduciary edges. The accuracy and failed detections were computed to evaluate the performance of the ST FIR BPF design using the Physionet database. It is observed that the designed ST FIR BPF was able to compute precise single fetus R-peaks and maternal R-peaks. The proposed ST filter can also be used for other ranged frequency signals other than biomedical electrical signals.

Design of Optimal FIR Filters Using Integrated Optimization Technique

The aim of the research work is to optimally design a finite impulse response (FIR) filter. For this purpose, an integrated optimization technique has been proposed. The proposed optimization technique integrates the Moth flame optimization (MFO) technique and Powell’s pattern search (PPS) technique in a coherent manner to maintain a fine balance between exploration and exploitation capabilities of the search technique. During the search process, the best performing MFO particle is transferred to the PPS method to avoid any possible stagnation. Initially, the proposed optimization technique has been tested on five standard test functions and then it is applied to design optimal FIR low-pass, high-pass, band-pass and band-stop filters. The performance of the proposed optimization technique is compared with other state of art optimization techniques and also with the results reported in the literature. The proposed optimization technique yields high-quality solution with minimal computational efforts. Further, student t test is applied to test the statistical performance of optimization technique and found satisfactory.

Comparison of spatial temporal representations of the vectorcardiogram using digital image processing

IntroductionThe vectorcardiography (VCG) is a method of representing the heart's electrical activity in three dimensions that is not frequently used in clinical practice due to the higher complexity compared to electrocardiography (ECG). A way around this problem was the development of regression techniques to obtain the VCG from the 12‑lead ECG and the evaluation of these techniques is done by comparing the parameters obtained by the gold standard method and by the VCG obtained by the alternative methods. In this paper it is proposed instead a comparison between the images of the VCG planes using the values returned by digital image processing metrics such as PSNR, SSIM and PW-SSIM. MethodsThe signals used were obtained from the Physikalisch-Technische Bundesanstalt Diagnostic ECG Database, which contains both the VCGs obtained by the gold standard method and the 12 lead ECG signals. They were divided into five groups that contained a control group and according to the region of the wall infarction. The ECG signals were then filtered using a Butterworth Finite Impulse Response bandpass filter, with cutoff frequencies of 3 Hz and 45 Hz and then the VCGs were by a computer application using the Kors inverse matrix method, the Kors quasi-orthogonal method and the Dower Inverse Matrix method. The reconstructed signals were then compared using the PSNR, SSIM and PW-SSIM methods. The returned values were presented in tables for each group containing the average value and standard deviance for each method in each VCG plane. ResultsUsing image processing techniques, it was possible to perceive that the alternative methods to obtain the VCG have a high confiability that could be compared to the gold standard in signals from healthy subjects. However, signals from pathological subjects present variations that could be caused by a deficit of these alternative methods to represent the pathology in these cases. Considering the PW-SSIM, the Frontal plane by the reconstructions was considered the most similar to the gold standard, having PW-SSIM values higher than 0.93 and for the Horizontal plane two groups had PW-SSIM values lower than 0.90 and for the Sagittal plane all groups had values lower than this value. DiscussionThe values yielded by the PSNR and SSIM had low variance, worsening the perception of the effect of the reconstruction method used or the infarction effect over the reconstruction. The values lower than 0.90 could indicate that these planes have their generation most affected by the infarction. ConclusionThe three methods of obtaining the VCG Frank leads, the Kors Quasi-Orthogonal method, the Kors Linear Regression method and the Dower Inverse Matrix, presented differences in the metrics: PSNR, SSIM and PW-SSIM in normal subjects according to the planes frontal, horizontal and sagittal and in subjects with Myocardial Infarction according to its topography: anterior, inferolateral, inferior or multiarterials. Considering only the PW-SSIM, the QO method had the best performance in different signals, followed by the Dower method.

Microwave-Induced Thermal Lesion Detection via Ultrasonic Scatterer Center Frequency Analysis with Autoregressive Cepstrum.

We proposed a new method for microwave-induced thermal lesion detection using the autoregressive spectrum analysis of ultrasonic backscattered signals in this paper. Eighteen cases of microwave ablation experiments and twenty cases of water bath heating experiments were conducted. Ultrasonic radiofrequency data of normal and coagulated porcine liver tissues were collected through these two experiments. Then, autoregressive spectrum analysis was performed; the mean frequency of the dominant peak in the autoregressive spectrum was computed based on water bath experiments; and a method for recognizing normal and solidified tissues was obtained by comparing the difference of the dominant peak in the autoregressive spectrum. Two bandpass finite impulse response filters, whose passbands corresponded respectively to the dominant peak in the autoregressive spectrum of normal and coagulated tissues, were used to compute the power spectral integration for the microwave-induced experiments. Microwave-induced thermal lesions were detected based on the differences between the power spectral integrations from the two filters. Compared to the caliper-measured area, the power spectral integration detected area had an error of (10.25 ± 3.59). Experimental results indicated that the proposed method may be used in preliminary detection of microwave-induced thermal lesions.

Experimental research on real-time acquisition and monitoring of wearable EEG based on TGAM module

Long-term sleep disorders can reduce the body’s immunity, induce various diseases, and seriously endanger human health Multi-conducting EEG (Electroencephalogram) sleep monitoring is the gold standard for evaluating the quality of sleep all night. However, this method is professional and complicated, and it is difficult to apply to daily sleep monitoring. This paper first designed a wearable EEG acquisition system based on TGAM module. ‘Through the parameter initialization setting of the TGAM module and the Bluetooth module and the analysis of the communication protocol between the modules, the wearable EEG acquisition system was successfully built. Secondly, the extraction of different rhythm waves of EEG signals is realized by several FIR (Finite Impulse Response) bandpass filters. Principal component analysis was used to screen feature quantities. The related experiments were carried out by collecting the EEG signals of several testers through the new sensor TGAM. Finally, event-related potential analysis and event-related simultaneous analysis were used to complete the treatment of EEG segments and normal EEG segments of sleep apnea events, and normalized EEG was identified by normalized standard deviation analysis and triple normalized standard deviation analysis. The results show that the technical requirements of wearable EEG equipment can be met in terms of algorithm calculation and result performance, which can provide theoretical support for sleep monitoring.

Fast Converging Cuckoo Search Algorithm to design symmetric FIR filters

Elimination of noise from transmitted signals inevitably incorporated during transmission persisted important task for the researchers from the preliminary days of Signal Processing. Among different techniques proposed regarding this purpose, use of digital filters has become most effectual in multiple ways. Feasible design, lower hardware costs have made the Finite Impulse Response (FIR) filters popular. Among different techniques, using perfect set of filter coefficients to implement FIR filters is most acceptable. Process of determining appropriate set of filter coefficients is characterized as an optimization problem with the objective of minimizing error function. Error function is conceptualized as an approximation function signifying deviancy between the designed filter responses from the ideal filter responses. Present work proposes Fast Converging Cuckoo Search Algorithm to obtain optimized filter coefficients to implement lowpass, highpass and bandpass FIR filters. Responses of the implemented filters using the proposed method are compared with the responses obtained by the filters designed using conventional Cuckoo Search Algorithm and Parks McClellan algorithm.

Design of Minimum-Phase FIR Filter: An Evolutionary Approach

In this communication, one novel attempt has been made towards the design of minimum-phase finite impulse response (FIR) filter using one evolutionary computation technique, named differential evolution (DE) algorithm. Mean square error (MSE) between the frequency samples of the ideal filter and the designed filter in the pass-band and stop-band region and the minimum average error (MAE) between the frequency samples in the transition-band region had been considered for the formulation of the objective function in the optimization process. Performance of the optimization technique has been monitored in terms of convergence characteristics for four different orders of FIR filter under consideration. Robustness of our proposition has been firmly established in the sense that the proposed algorithm can be suitably tuned for the design of low-pass, high-pass or band-pass FIR filter of different specifications. Supremacy of the proposed algorithm over other existing techniques for the design of minimum-phase FIR filter has been substantiated by means of frequency response and pole-zero diagrams.

Current Status and Issues Regarding Pre-processing of fNIRS Neuroimaging Data: An Investigation of Diverse Signal Filtering Methods Within a General Linear Model Framework.

Functional near-infrared spectroscopy (fNIRS) research articles show a large heterogeneity in the analysis approaches and pre-processing procedures. Additionally, there is often a lack of a complete description of the methods applied, necessary for study replication or for results comparison. The aims of this paper were (i) to review and investigate which information is generally included in published fNIRS papers, and (ii) to define a signal pre-processing procedure to set a common ground for standardization guidelines. To this goal, we have reviewed 110 fNIRS articles published in 2016 in the field of cognitive neuroscience, and performed a simulation analysis with synthetic fNIRS data to optimize the signal filtering step before applying the GLM method for statistical inference. Our results highlight the fact that many papers lack important information, and there is a large variability in the filtering methods used. Our simulations demonstrated that the optimal approach to remove noise and recover the hemodynamic response from fNIRS data in a GLM framework is to use a 1000th order band-pass Finite Impulse Response filter. Based on these results, we give preliminary recommendations as to the first step toward improving the analysis of fNIRS data and dissemination of the results.

Linear phase FIR filter to compute fetal heart rate variability

Continuous monitoring of fetal heart rate (FHR) can detect the well-being of the fetus and thus indicates non-reassuring fetal status. In- vasive fetal electrocardiography (FECG) using the fetal scalp electrode applied to the fetus scalp allows accurate detection of fetal QRS (FQRS) complexes, however with a risk of infection to the fetus. We have proposed a non-invasive fetal heart rate (NIFHR) filtering technique employing finite impulse response (FIR) filters. We applied Fast Fourier Transform (FFT) to the Physionet abdominal ECG (aECG) records and derived the fiduciary edges of the spectrum of the FECG. A FIR band pass filter (BPF) is designed which is a com- posite filter consisting of a high pass filter (HPF) followed by a low pass filter (LPF) in that order. The cut off frequencies of these com- posite filters are the fiduciary edges of the fetal electrocardiography spectrum. A FQRS detector to obtain fetal heart rate variability (FHRV) processes the FQRS signal filtered through these composite FIR filters. It is observed that channel 4 from records r01 and r08 obtained 100% results for sensitivity, positive predictive value and accuracy while, the overall accuracy was 92.21%. This design can also be extended to compute maternal heart rate.

Design FIR Band Pass Filter With Centered At 50 Hz For Medical Application

Digital signal processing techniques used widely to cancel undesired parts of the signals, like that interference with other frequency range. Electromagnetic signals can be interference with human body signals such as Electrocardio signal Electroencephalogram and Electromyography. These interferences can be affect on the diagnosis signal during the examination and when these happen with different frequencies,such as (EMG) noise, devices that have high vibration which give fault data or effect the final result. Filtering of signals interference is very useful in the diagnosis of biomedical cases, as instant as the ECG signal that represent weak signal. This work treat problems of all kinds of interference with ECG signal and reduce it based on the development of digital Finite Impulse Response (FIR)filter for ECG signal which has the frequency between (5Hz to 100 Hz)using fdtool by MATLAB instead of classical filters that often unaccurate. It is hard to get pure signal from human body without any interferences specially with that range of frequencies. In this paper the ECG signal has been presented from human body with its frequency spectrums before filtering then filtered from unwanted frequencies and show the elimination of the disturbance interference from this signal

The gravity field model IGGT_R1 based on the second invariant of the GOCE gravitational gradient tensor

Based on tensor theory, three invariants of the gravitational gradient tensor (IGGT) are independent of the gradiometer reference frame (GRF). Compared to traditional methods for calculation of gravity field models based on the gravity field and steady-state ocean circulation explorer (GOCE) data, which are affected by errors in the attitude indicator, using IGGT and least squares method avoids the problem of inaccurate rotation matrices. The IGGT approach as studied in this paper is a quadratic function of the gravity field model’s spherical harmonic coefficients. The linearized observation equations for the least squares method are obtained using a Taylor expansion, and the weighting equation is derived using the law of error propagation. We also investigate the linearization errors using existing gravity field models and find that this error can be ignored since the used a-priori model EIGEN-5C is sufficiently accurate. One problem when using this approach is that it needs all six independent gravitational gradients (GGs), but the components $$V_{xy}$$ and $$V_{yz}$$ of GOCE are worse due to the non-sensitive axes of the GOCE gradiometer. Therefore, we use synthetic GGs for both inaccurate gravitational gradient components derived from the a-priori gravity field model EIGEN-5C. Another problem is that the GOCE GGs are measured in a band-limited manner. Therefore, a forward and backward finite impulse response band-pass filter is applied to the data, which can also eliminate filter caused phase change. The spherical cap regularization approach (SCRA) and the Kaula rule are then applied to solve the polar gap problem caused by GOCE’s inclination of $$96.7^{\circ }$$ . With the techniques described above, a degree/order 240 gravity field model called IGGT_R1 is computed. Since the synthetic components of $$V_{xy}$$ and $$V_{yz}$$ are not band-pass filtered, the signals outside the measurement bandwidth are replaced by the a-priori model EIGEN-5C. Therefore, this model is practically a combined gravity field model which contains GOCE GGs signals and long wavelength signals from the a-priori model EIGEN-5C. Finally, IGGT_R1’s accuracy is evaluated by comparison with other gravity field models in terms of difference degree amplitudes, the geostrophic velocity in the Agulhas current area, gravity anomaly differences as well as by comparison to GNSS/leveling data.

Harmonic Analysis Algorithm Based On SVD Filter

SVD (singular value decomposition) has been applied to design a FIR bandpass filter for both narrow and steep transitional bands, so as to simplify the complex execution on hardware when the harmonic algorithm that is based on FIR (finite impulse response) digital filter is used. First of all, a conventional method is used to obtain the coefficients of the band-pass filter (prototype), and some of the coefficients are arranged in a matrix. Then, the coefficient matrix is used to calculate SVD, based on which, a low dimensional and approximate expression of the matrix is accordingly obtained. Finally, according to the approximate expression of the matrix, the execution structure of the extrapolation filter is employed to design, approximately, the prototype of the band-pass filter. Simulation results show that the complex hardware execution of the harmonic algorithm can be simplified by using the proposed method to extract and analyze the harmonic waves.

Rail-to-Rail-Input Dual-Radio 64-Channel Closed-Loop Neurostimulator

A 64-channel 0.13- $\mu \text{m}$ CMOS system on a chip (SoC) for neuroelectrical monitoring and responsive neurostimulation is presented. The $\Delta \Sigma $ -based neural channel records signals with rail-to-rail dc offset at the input without any area-intensive dc-removing passive components, which leads to a compact 0.013-mm2 integration area of recording and stimulation circuits. The channel consumes 630 nW, yields a signal to noise and distortion ratio of 72.2 dB, a 1.13- $\mu $ Vrms integrated input-referred noise over 0.1–500 Hz frequency range, and a noise efficiency factor of 2.86. Analog multipliers are implemented in each channel with minimum additional area cost by reusing the multi-bit current-digital to analog converter that is originally placed for current-mode stimulation. The multipliers are used for compact implementation of bandpass finite impulse response filters, as well as voltage gain scaling. A tri-core low-power DSP conducts phase-synchrony-based neurophysiological event detection and triggers a subset of 64 programmable arbitrary-waveform current-mode stimulators for subsequent neuromodulation. Two ultra-wideband (UWB) wireless transmitters communicate to receivers located at 10 cm to 2 m distance from the implanted SoC with data rates of 10–46 Mb/s, respectively. An inductive link that operates at 1.5 MHz provides power to the SoC and is also used to communicate commands to an on-chip ASK receiver. The chip occupies 6 mm2 while consuming 1.07 and 5.44 mW with delay-based and voltage controlled oscillator-based UWB transmitters, respectively. The SoC is validated in vivo using epilepsy monitoring (seizure detection) and treatment (seizure suppression) experiments.

Влияние режекторного фильтра на эффективность линеаризации фазочастотной характеристики аналогового полосового фильтра

The previously published works of the authors dealt with methods aimed at linearizing the phase frequency responses of analog filters using digital linearizing finite impulse response (FIR) filters. If the operating frequency band contains narrow-band interference, such interference often needs to be suppressed by using a narrow-band analog band-stop filter. However, when a band-stop filter is connected in series, the linearized phase frequency response may become distorted. The article examines the influence of a narrow-band analog band-stop filter on the effectiveness of linearizing the phase frequency responses of a complex analog band-pass filter using a complex band-pass linearizing digital FIR filter. The study was conducted using a circuit simulation program based on a model consisting of the following modules: a complex analog band-pass filter with a sixth-order Butterworth low-pass filter prototype, a narrow-band complex analog band-stop filter with a third-order Butterworth low-pass filter prototype, and a complex digital band-pass linearizing FIR filter. The article presents the results from studying the frequency band in which the phase frequency response linearity is distorted to an acceptable degree. A sharp change in the group delay time level takes place in the stopband vicinity. The frequency band in which the group delay ripple is larger than the pre-linearization group delay ripple is referred to as the linearization effect loss band. If the difference between the band-stop filter’s passband boundary frequencies is much (by dozens of times) smaller than the band of the complex band-pass filter, the linearization effect is retained over most of the passband. With the selected parameters and orders of the complex analog filter and band-stop filter, the frequency band in which the linearization effect vanishes is approximately seven times greater than the difference between the band-stop filter’s passband boundary frequencies. Such an approach is relevant in filtering narrow-band interference within the frequency band of broadband signals.

Design and implementation of an efficient FIR digital filter

AbstractDigital signal processing (DSP) circuits are extremely important in computing and communications areas. One application of DSP is a Finite impulse response (FIR) filter. The principle objective of this exploration is to present a methodology for an upgraded framework of a FIR digital filter from software level to the hardware level. It includes the selection of design method, structure and cost effective hardware utilization. Theoretical and experimental results performed FIR band pass filter suggests that the window design method is relatively simple and easy to use because of the availability of well-defined equation. Comparison presented that Kaiser window gives the minimum main-lobe width and a sharp cut-off which means this window has less transition width and the study showed that the Direct-Form structure approach is simpler and offers a better performance than other common filter structures. It results in low cost, reduced area and more robust to withstand the quantization errors. For effi...