Finite Impulse Response Research Articles

Low-Power Reconfigurable FIR Filter Design Based on Common Operation Sharing

This paper presents a low-power, fully reconfigurable finite impulse response (FIR) filter structure based on common operation sharing. Different from existing multiplexer(MUX)-based designs, the decoding of coefficients and compensation of negative-coefficient errors, which are the common operations for all the taps, are implemented by shared modules to reduce the overall hardware complexity. To validate the proposed structure, a proof-of-concept reconfigurable FIR filter is implemented and fabricated using 40 nm CMOS technology. Chip measurement results show that the proposed design is superior to existing methods in area-delay product and power performance, making it suitable for low-power filtering applications. The idea of sharing common operations for all taps can benefit the existing MUX-based filter techniques for further improvement of power and circuit complexity.

Segmented Silicon Modulator With a Bandwidth Beyond 67 GHz for High-Speed Signaling

We demonstrate an all-silicon segmented modulator with traveling-wave electrodes, achieving an electro-optic bandwidth beyond 67 GHz and a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V_\pi$</tex-math></inline-formula> of 5V. We show that dividing a long optical modulator into shorter segments can help achieve a higher bandwidth without compromising modulation efficiency or optical loss. We analyze the bandwidth limitation due to the delay mismatch between the driving and optical signals. We show that the impact of misalignment of driving delays between segments on the overall bandwidth of the modulator can be described by a finite impulse response filter. Using this modulator, we achieve optical transmission of 120 Gbaud 8-level amplitude shift keying with coherent detection. Taking into account the forward error correction overhead, this yields 336.4 Gb/s net on a single polarization. Our design has the potential for achieving 1 Tb/s using dual-polarization IQ modulation.

A novel fusion maximum correntropy Kalman/UFIR filter for state estimation with uncertain non-Gaussian noise statistics

Despite the higher estimation accuracy of the maximum correntropy Kalman filter (MCKF) algorithm in system with non-Gaussian noise, its estimation performance will decrease when the noise source changes due to disturbances from external uncertainties. Fortunately, the unbiased finite impulse response predictor (UFIR) can overcome the MCKF problems by automatically ignoring the noise related to both the process and measurements. Meanwhile, the MCKF could resolve the UFIR problems, such as non-optimal estimation performance and risk of dead zones. Therefore, a novel fusion maximum correntropy Kalman/UFIR filter is proposed to achieve a more advantageous estimation effect, in which specific probability weights are assigned to the two filters to implement the fusion of two filters. The simulation results demonstrate the superiority of the presented fusion filter algorithm when compared to the fusion Kalman/UFIR filter regarding the estimation performance under the non-Gaussian noise system.

A Performance of AFIRO among Asynchronous Iteration Strategy Metaheuristic Algorithms

Asynchronous Finite Impulse Response Optimizer (AFIRO) is a metaheuristic algorithm that has been developed as a population-based solution with an asynchronous update mechanism. AFIRO is inspired by the Ultimate Unbiased Finite Impulse Response filter framework. AFIRO works with a group of agents where each agent performs the iteration update asynchronously. In the original paper, AFIRO was compared with the Particle Swarm Optimisation algorithm, Genetic Algorithm, and Grey Wolf Optimizer. Although AFIRO shows a better performance, the comparison seems unfair since the iteration strategy of AFIRO is different from those compared algorithms. Hence, this article further investigates the potential of AFIRO against three existent metaheuristic algorithms with the same iteration strategy, namely Asynchronous PSO (A-PSO), Asynchronous Gravitational Search Algorithm (A-GSA), and Asynchronous Simulated Kalman Filter (A-SKF). The CEC2014 test suite was applied to evaluate the performance, where the results revealed that AFIRO leads 18 out of 30 functions. The Holm post hoc showed that AFIRO performs significantly better than A-SKF and A-GSA while having the same performance as A- PSO. Moreover, the Friedman test disclosed that AFIRO has the highest ranking than A-PSO, A-SKF, and A-GSA. Therefore, it can be concluded that AFIRO performs well in the same iteration strategy category.

Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents.

Underwater sensor networks play a crucial role in collecting valuable data to monitor offshore aquaculture infrastructures. The number of deployed devices not only impacts the bandwidth for a highly constrained communication environment, but also the cost of the sensor network. On the other hand, industrial and literature current meters work as raw data loggers, and most of the calculations to determine the fundamental frequencies are performed offline on a desktop computer or in the cloud. Belonging to the edge computing research area, this paper presents an algorithm to extract the fundamental frequencies of water currents in an underwater sensor network deployed in offshore aquaculture infrastructures. The target sensor node is based on a commercial ultra-low-power microcontroller. The proposed fundamental frequency identification algorithm only requires the use of an integer arithmetic unit. Our approach exploits the mathematical properties of the finite impulse response (FIR) filtering in the integer domain. The design and implementation of the presented algorithm are discussed in detail in terms of FIR tuning/coefficient selection, memory usage and variable domain for its mathematical formulation aimed at reducing the computational effort required. The approach is validated using a shallow water current model and real-world raw data from an offshore aquaculture infrastructure. The extracted frequencies have a maximum error below a 4%.

Application-Specific Integrated Circuit of an Inter-IC Sound Digital Filter for Audio Systems

In digital audio systems, filters and equalizers are essential modules for audio improvement at the input and output stages. Due to their computational complexity, most audio tasks are processed with digital signal processors. Due to the fact that latency in audio systems is a critical specification and audio trends require higher sample rates, noise canceling, and bigger data sizes, having an independent high-resolution equalizer would reduce the computational power needed for audio systems. This research had the goal of designing and implementing a hardware architecture for a configurable filter bank based on finite impulse response (FIR) filters and a noise-cancellation stage with an inter-integrated circuit (I2C) communication interface, which allows the filter configuration. The system was implemented as a standalone integrated circuit (IC) for which its inputs were the inter-IC sound (I2S) bus control signals. The digital audio system was optimized to perform one-cycle convolutional operations by implementing a vector–vector arithmetic logic unit. Furthermore, this applied research provides the register transfer level description and the functional verification of the digital design, the system-on-chip (SoC) implementation in TSMC 180 nm technology, and the post-silicon validation with a printed circuit board for testing the output digital signals of the system.

Research on Channelization Techniques of Radio Astronomical Wideband Signal with Oversampled Polyphase Filter Banks

Digital channelization decomposes a wideband signal into multiple adjacent sub-bands using Parallel Technology. Channelization can effectively reduce the pressure on the radio astronomy digital backends system and make wideband signal processing possible. Aiming at the problems of signal attenuation at sub-band edge, spectral leakage and aliasing encountered in wideband signal channelization, algorithms to reduce the problems are studied. We design a Critically Sampled Polyphase Filter Bank (CS-PFB) based on the Finite Impulse Response digital filter with a Hamming Window and systematically analyze the frequency response characteristics of the CS-PFB. Based on the channelized structure of the CS-PFB, an OverSampled Polyphase Filter Bank (OS-PFB) is designed by data reuse, and the filtering frequency response characteristics of CS-PFB and OS-PFB are compared and analyzed. Using the wideband baseband data generated by the CASPSR (Collaboration for Astronomy Signal processing and electronics research Parkes Swinburne Recorder), we implement sub-band division and 16-band output of these data based on the 2× oversampling OS-PFB, and the problem of spectrum inversion in the sub-bands is corrected. After removing 25% of redundant data in the head and tail of each sub-band, we recombine the sub-bands into a wideband. The wideband signal is almost identical to the original observed signal. Therefore, the experimental results show that the OS-PFB can improve the channel response. For the 400 MHz baseband data of J0437-4715, we compare the pulse profile obtained from the original baseband data with the pulse profile obtained after the channelization and recombination. The phase and amplitude information of the pulse profiles are consistent, which verifies the correctness of our channelization algorithm.

A Multi-Box Behavioural Nonlinear Mixer Model

ABSTRACT This paper presents a new behavioural mixer model in a multi-box structure. In the proposed model, as well as amplitude and phase nonlinearity, the memory effect is also modelled. The multi-box structure is constructed in line with the Hammerstein model to characterise both fundamental signals, intermodulation distortion (IMD) and harmonic distortion (HD) for mixers in particular and all frequency translating devices in general. A testbed is constructed to measure both amplitude and phase characteristics. A good match between the measured and the calculated results is obtained using curve fitting and optimisation algorithms. In order to model the memory effect, a finite impulse response (FIR) filter is used. The measured IM3 imbalance is successfully modelled with this filter. For fundamental components, amplitude and phase errors are less than 0.1 dB and 1 degree, respectively. For IM3 components, amplitude and phase errors are less than 4 dB and 10 degrees, respectively. For the overall accuracy of the model, measurements are conducted with two-tone and modulated signals, and normalised mean square error (NMSE) values are calculated as −31.5 dB and −29.3 dB, respectively. The results are obtained for a wide range of input power span, including the compression region where nonlinearity is strongly pronounced. The proposed model is capable of accurately representing nonlinearity and memory effect for mixers and frequency translating devices in general and thus may be used for system-level modelling and linearisation applications.

Athermal, fabrication-tolerant Si-SiN FIR filters for a silicon photonics foundry platform.

A means of athermalizing unbalanced Mach-Zehnder interferometers on a 300 mm silicon photonics foundry platform utilizing Si and SiN layers to produce the path imbalance is demonstrated. This technique can be applied to all other forms of finite impulse response filters, such as arrayed waveguide gratings. Wafer scale performance of fabricated devices is analyzed for their expected performance in the target application: odd-even channel (de)-interleavers for dense wavelength division multiplexing links. Finally, a method is proposed to improve device performance to be more robust to fabrication variations while simultaneously maintaining athermality.

Development of a design optimization algorithm for a bowtie antenna

A bowtie antenna is one of the simple dipole antennas with an omnidirectional pattern utilized in several applications. It is used in industrial applications, scientific applications, and medical applications. Its elementary design can be subjected to modification to expand the applications of the dipole and improve its performance. This paper aims to develop a design optimization algorithm for a bowtie antenna with an adaptive finite impulse response (FIR) filter. In the paper, the different designs of the bowtie antenna are simulated using MATLAB software. The design of antennas is constructed using the partial differential equation (PDE) toolbox in MATLAB software. The designs explored in the paper are the slotted microstrip bowtie antenna and the double flare bowtie antenna. A traditional bowtie was also simulated to be used as a reference for the evaluation of the modified antennas. The dimensions of the designs are kept closely like draw accurate conclusions about the effects of the refinements done. The effects of the modification of the designs on the directivity and return loss are determined to assess the effectiveness of the design alterations.

Development of an adaptive finite impulse response filter optimization algorithm using rough set theory

Signal processing is crucial that as one sends information, there is a corresponding process to encode, decode, and clean the signal of unwanted noise and disruptions via use of filters. Due to the environment and how unpredictable it can be and how noise can come from almost anywhere, the typical filter to be used are adaptive filters. Adaptive filters are non-linear filters and have been used regularly regarding adaptive signal processing, this means that the filter changes accordingly and adapts to the environmental noise surrounding it. The world today has numerous applications for adaptive filters such as channel equalization and acoustic noise cancellation. This incentivizes the further development of this specific technology and the constant research that is ongoing. The main component when it comes to adaptive filtering is the algorithms used for the filter. This research compares the least mean square (LMS) and recursive least square (RLS) algorithms concerning their effectiveness in filtering out unwanted acoustic noises. The paper will cover the design and implementation of an optimized rough set based adaptive finite impulse response (FIR) filter for acoustic noise cancellation. The microstrip and bowtie antenna were used to relay the data. The software MATLAB was used for the simulation.

3P4W Grid Interactive PV-BES System With Seamless Transition Capability

For seamless transition of 3P4W (three phase four-wire) grid interactive solar photovoltaic (PV) system, a suboptimal finite impulse response (FIR) filter with approximation based on infinite impulse response filter (IIR) is employed here. The need for power quality improvement is essential and in order to guarantee an improved PQ, the grid currents are analyzed in covenant with the IEEE-519 standard. The power transfer proficiency with suboptimal filter utilization reduced intermittency associated with renewable sources along with improved power quality. Moreover, with the rise in the usage of distributed energy resources involving renewable energy sources, the need for power quality improvement is paramount. The need for improving PQ, stems from the fact that an uninterrupted supply is essential to the critical loads along with an improved power quality. Therefore, during operating modes such as grid linkage/interruption, the utilization of an efficient control is mandatory. Moreover, the behavior is required to be in agreement with the IEEE-519 and IEEE-1547 standards and in off-grid mode, a voltage controller is utilized for the power transfer. Thus, with adequate performance during the weak grid conditions, corroboration of satisfactory system behavior is obtained.

A capacitance sensing method with trans-impedance based readout circuit and adaptive filtering for micro-gyro

Trans-impedance amplifier (TIA) based capacitance–voltage (C–V) readout circuit is an attractive choice for micro-machined gyroscope for its simplicity and superior performance. In this work, the noise and the C–V gain characteristics of the TIA circuit are analyzed in detail. Then, a TIA based readout circuit with a C–V gain of about 286 dB is designed, and a series of experiments are conducted to test the performance of the circuit. Both the analysis and test results show that T-network TIA should be avoided as far as possible for its poor noise performance. All results also show that there is a signal-to-noise ratio (SNR) limit for the TIA based readout circuit, and the SNR can only be further improved by filtering. Hence, an adaptive finite impulse response filter is designed to further improve the SNR of the sensed signal. For a gyroscope with a peak-to-peak variable capacitance of about 200 aF, a SNR of 22.8 dB can be achieved by the designed circuit and a SNR of 47 dB can be obtained by further adaptive filtering. Finally, the solution presented in this paper achieves a capacitive sensing resolution of 0.9 aF.

A Novel Kernel Algorithm for Finite Impulse Response Channel Identification

&#x0D; &#x0D; &#x0D; &#x0D; Over the last few years, kernel adaptive filters have gained in importance as the kernel trick started to be used in classic linear adaptive filters in order to address various regression and time-series prediction issues in nonlinear environments.In this paper, we study a recursive method for identifying finite impulse response (FIR) nonlinear systems based on binary-value observation systems. We also apply the kernel trick to the recursive projection (RP) algorithm, yielding a novel recursive algorithm based on a positive definite kernel. For purposes, our approach is compared with the recursive projection (RP) algorithm in the process of identifying the parameters of two channels, with the first of them being a frequency-selective fading channel, called a broadband radio access network (BRAN B) channel, and the other being a a theoretical frequency-selective channel, known as the Macchi channel. Monte Carlo simulation results are presented to show the performance of the proposed algorithm.&#x0D; &#x0D; &#x0D; &#x0D;

Ultrasonic defect detection of high-density polyethylene pipe materials using FIR filtering and block-wise singular value decomposition

Condition monitoring of high-density polyethylene (HDPE) pipes used for fluid and gas transfer is important for the safety of energy conservation and the environment. Ultrasonic phased array imaging methods provide a solution to detect and assess defects in HDPE pipes. However, ultrasonic bulk waves propagating in these viscoelastic media are strongly attenuated, resulting in reduced signal amplitude. In this study, a linear-phase Finite Impulse Response (FIR) filter is used to remove unwanted frequency components from the measured ultrasonic signals to improve the signal-to-noise ratio before applying the imaging algorithm of the total focusing method (TFM). Building upon this, a block-wise singular value decomposition (SVD) technique, which can adaptively determine the singular value cutoff threshold based on each block in the whole TFM image, is used to enhance the obtained TFM image quality. The performance of the combination of FIR filtering and block-wise SVD technique is validated by experimental data of HDPE pipe materials. Results demonstrate that the proposed approach generates good images to provide the detection and characterization of side-drilled holes in HDPE pipe materials.

Development of variable 2D FIR filter structures using farrow approximation and row-wise polyphase decomposition

This work proposes pre and post Farrow approximation of row-wise polyphase decomposed 2D finite impulse response (FIR) filters to achieve variability in 2D bandwidths with low implementation costs. The proposed method starts with realizing variable 2D filters using the 2D Farrow structure. The 2D Farrow filter structure is then row-wise polyphase decomposed and approximated in terms of fractional delay again to obtain the final set of coefficients. To illustrate the efficiency of the proposed methodology, design examples of variable circular and elliptical filters are provided in this paper. The simulation results show that the proposed methodology can result in variable 2D FIR filters with a considerable reduction in the number of multipliers w.r.t the existing approaches without much degradation in the performance parameters.

Robust Arm Impedocardiography Signal Quality Enhancement Using Recursive Signal Averaging and Multi-Stage Wavelet Denoising Methods for Long-Term Cardiac Contractility Monitoring Armbands.

Impedance cardiography (ICG) is a low-cost, non-invasive technique that enables the clinical assessment of haemodynamic parameters, such as cardiac output and stroke volume (SV). Conventional ICG recordings are taken from the patient's thorax. However, access to ICG vital signs from the upper-arm brachial artery (as an associated surrogate) can enable user-convenient wearable armband sensor devices to provide an attractive option for gathering ICG trend-based indicators of general health, which offers particular advantages in ambulatory long-term monitoring settings. This study considered the upper arm ICG and control Thorax-ICG recordings data from 15 healthy subject cases. A prefiltering stage included a third-order Savitzky-Golay finite impulse response (FIR) filter, which was applied to the raw ICG signals. Then, a multi-stage wavelet-based denoising strategy on a beat-by-beat (BbyB) basis, which was supported by a recursive signal-averaging optimal thresholding adaptation algorithm for Arm-ICG signals, was investigated for robust signal quality enhancement. The performance of the BbyB ICG denoising was evaluated for each case using a 700 ms frame centred on the heartbeat ICG pulse. This frame was extracted from a 600-beat ensemble signal-averaged ICG and was used as the noiseless signal reference vector (gold standard frame). Furthermore, in each subject case, enhanced Arm-ICG and Thorax-ICG above a threshold of correlation of 0.95 with the noiseless vector enabled the analysis of beat inclusion rate (BIR%), yielding an average of 80.9% for Arm-ICG and 100% for Thorax-ICG, and BbyB values of the ICG waveform feature metrics A, B, C and VET accuracy and precision, yielding respective error rates (ER%) of 0.83%, 11.1%, 3.99% and 5.2% for Arm-IG, and 0.41%, 3.82%, 1.66% and 1.25% for Thorax-ICG, respectively. Hence, the functional relationship between ICG metrics within and between the arm and thorax recording modes could be characterised and the linear regression (Arm-ICG vs. Thorax-ICG) trends could be analysed. Overall, it was found in this study that recursive averaging, set with a 36 ICG beats buffer size, was the best Arm-ICG BbyB denoising process, with an average of less than 3.3% in the Arm-ICG time metrics error rate. It was also found that the arm SV versus thorax SV had a linear regression coefficient of determination (R2) of 0.84.

Short line segment interpolation by using velocity blending technology with high overlapping time

In this study, a novel highly overlapping time technology (HOTT) that uses the velocity blending method is proposed to generate interpolated trajectories for motion control. This technique uses overlapping time to blend the velocities between short line segments. To ensure that the acceleration constraints and corner tolerance are satisfied, HOTT provides a systematic algorithm with derived equations to adjust the overlapping time. Compared with a finite impulse response approach, HOTT achieves higher feedrates, lower tolerance, and maximum acceleration. Simulation and experimental results reveal that HOTT yields a shorter cycle time and higher contour accuracy.

Design and Performance Analysis of RNS-Based Reconfigurable FIR Filter for Noise Removal in Speech Signals Applications

In DSP solutions, the Residual Number System with Two's Complement systems is the most commonly utilized system for building low-power and high-throughput programmable Finite Impulse Response filters. It would be done by creating FIR filters in the Residual Number organization and 2's Enhance scheme by comparing the results to the current assert. The RNS based on FIR filter architecture reduces power consumption while allowing the device to operate at 150 MHz without increasing its size significantly. In case of memory and latency reduction, the implementations of the Residual Number System and 2's Complement System must be able to obtain and decode signals with fewer physical servers for every clock signal. The principal idea of this proposed model is to provide data bits with larger sizes for RNS-based multiplier and delayed wavelet LMS (DWLMS) that operates at speed high with premised reconfigurable FIR via forward and reverse conversions that don't produce as much power output and size as reflective thinking. The Application Specific Integrated Circuit will be designed and integrated for 32 nm technology. The proposed design addresses the four essential parameter optimization, such as power, area, and timing, using the Residual Number System, which is superior to Two's Complement System. According to the findings, there is a 13 percent reduction in power, a 21 % enhancement in area, and a 13 % enhance in throughput.

Online evaluation of resistance spot welding quality and defect classification

Resistance spot welding (RSW) is widely used in industrial product manufacturing, and weld quality is critical to ensure the safety and reliability of mechanical structures. With product quality improvement, the online monitoring of weld quality has become an urgent issue. Therefore, a method for online evaluation of RSW quality and automatic classification of welding defects based on mild steel is proposed. By acquiring the welding current and electrode voltage signals of the welding process in real time, a finite impulse response low-pass filter based on the Blackman window function is designed to perform zero-phase filtering of the dynamic resistance (DR). The influence of three welding parameters on the nugget diameter and shear strength of spot welding of DC01 mild steel was studied through the control variable method to determine the optimum welding parameters. Since the main defects of the RSW process are classified as expulsion defects and incomplete fusion defects, minor adjustments were made to the welding parameters to produce expulsion and incomplete fusion defects. Features in the time domain are extracted from the DR curves signals of normal, expulsion, and incomplete fusion welding spots, and the performance of the extracted features in the classifier is analyzed. Improvements are made to classify normal and expulsion spots with low accuracy, a new method is proposed that can accurately classify the quality of the welding spots. Through online evaluation tests of quality on 200 welding spots, the online evaluation test showed results that closely matched the validation test results. The results of the classification performance tests show that this study can be used for online evaluation of RSW quality and automatic classification of the welding spot defects of the DC01.