Design Of Digital Filters Research Articles

A Projection Technique for The Design of Fir Digital Filters.(Dept.E)

A method for synthesis of chebyshev FIR digital filters is presented. The best approximation in the chebyshev (L ) sense is obtained making use of the method of successive projections, which reduces the problem to one of finding a point in the intersection of a system of convex sets. The metrios is fast converging and does not require solving a set of non-linear equations as in other minimax techniques.

Low complexity multiobjective finite impulse response filter design using Salp swarm algorithm and its improved version

AbstractRecent trend indicates that the assessment of low complexity is crucial for an effectual design of digital filter. Earlier the existing algorithms solely focused on reducing the pass band ripples and the stop band ripples in spite of the requirement of low implementation complexity in finite impulse response (FIR) filter design. In this regard, the optimization‐based FIR filter using multiobjective improved Salp swarm optimization algorithm have been designed. The proposed method not only minimizes the ripples of pass band and stop band but also minimizes the transition band, number of sparsity, which is used to implement a FIR filter that abides the specified frequency. The nondominated solution of filter design has a set of an optimum solution as pareto front that maintains the trade‐off between the various specifications. The designed FIR filter has been compared with other reported method to validate the applicability of the proposed method. The evaluation and analysis have been performed regrading minimum pass band ripples, minimum stop band ripple, minimum transition band, and implementation complexity. To prove the practical applicability of the proposed method, the designed FIR filters have been implemented in Xilinx ISE14.7 (Virtex‐VII) environment. The comparison result shows that the proposed method performs better than all other reported method in achieving minimum ripples and implementation complexity.

About This Issue

May 31 2022 About This Issue Author and Article Information Online Issn: 1531-5169 Print Issn: 0148-9267 © 2022 Massachusetts Institute of Technology2022Massachusetts Institute of Technology Computer Music Journal (2022) 45 (2): 1–2. https://doi.org/10.1162/comj_e_00602 Cite Icon Cite Permissions Share Icon Share Twitter LinkedIn Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation About This Issue. Computer Music Journal 2022; 45 (2): 1–2. doi: https://doi.org/10.1162/comj_e_00602 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsComputer Music Journal Search Advanced Search This issue’s articles each consider a different area of audio processing. The first three deal with specific signal-processing techniques in the areas of filtering, spatialization, and synthesis, respectively. The fourth concerns data mining in audio corpora, typically employing descriptors obtained from signal processing. In the first article, Lazzarini and Timoney present their digital filter designs that are derived from analog filters. The authors contend that examining the high-level block diagrams and transfer functions of an analog model can yield benefits not found in the “virtual analog” approach of attempting to analyze and reproduce every detail of a specific analog circuit. As evidence, they offer both linear and nonlinear versions of a digital filter derived from the analog state variable filter. They then extend the nonlinear design to a filter that goes beyond the analog model by incorporating ideas stemming from waveshaping synthesis. In the area of spatialization, the article by... You do not currently have access to this content.

Design and Implementation of Third Order Low Pass Digital FIR Filter using Pipelining Retiming Technique

This paper presents design and implementation of 3rd order low pass digital FIR filter using pipelining retiming technique. Aim of this paper is to apply pipelining retiming technique on low pass digital FIR filter and compare with the existing second order retimed FIR filter and third order broadcast, non-broadcast low pass FIR filter. MATLAB FDA tool is used to calculate digital FIR filter coefficients. Hamming and Kaiser window methods are used to find out the coefficients of the FIR filter. Broadcast and non broadcast third order low pass FIR filter architectures are used for pipelining retiming .Cutset and feed forward pipelining retiming techniques are used to retime the third order low pass digital FIR filter. We design our algorithm in VHDL and implemented on Xilinx Vivado xc7a35tcpg261-1. Area (LUT), speed and power are calculated using Xilinx Vivado 2015.2 tool. Synthesis and simulation results are discussed in this paper. Speed and area (LUT) of proposed third order low pass FIR filter is improved in comparison with existing designs.

A survey of optimal polynomial approximants, applications to digital filter design, and related open problems

In the last few years, the notion of optimal polynomial approximant has appeared in the mathematics literature in connection with the Hilbert spaces of analytic functions of one or more variables. In the 1970s, researchers in engineering and applied mathematics introduced least-squares inverses in the context of digital filters in signal processing. It turns out that in the Hardy space \(H^{2},\) these objects are identical. This paper is a survey of known results about optimal polynomial approximants. In particular, we will examine their connections with orthogonal polynomials and reproducing kernels in weighted spaces and digital filter design. We will also describe what is known about the zeros of optimal polynomial approximants, their rates of decay, and convergence results. Throughout the paper, we state many open questions that may be of interest.

FIR FILTER DESIGN WITH INERTIA WEIGHT AND COMPRESSION FACTOR APPROACH USING ADVANCED OPTIMIZATION TECHNIQUES

This paper includes the design of Finite impulse response filter with inertia weight and compression factor approach. The objective function of filter design involves accurate control of various parameters of frequency spectrum and is thus highly non-uniform, non-linear, non-differentiable and multimodal in nature. Classical optimization methods cannot converge to solutions. Because they have disadvantages such as highly sensitive to starting points, frequent convergence to local optimum solution or divergence or revisiting the same solution, requirement of continuous and differentiable objective cost function, requirement of the piecewise linear cost approximation and problem of convergence and algorithm. Evolutionary optimization methods for the design of optimal digital filters have better control of parameters and the highest stop band attenuation.

Digital FIR Filter Design by PSO and its v ariants Attractive and Repulsive PSO(ARPSO) & Craziness based PSO(CRPSO)

Digital filters play a major role in signal processing that are employed in many applications such as in control systems, audio or video processing systems, noise reduction applications and different systems for communication. In this regard, FIR filters are employed because of frequency stability and linearity in their phase response. FIR filter design requires multi-modal optimization problems. Therefore, PSO (Particle Swarm Optimization) algorithm and its variants are more adaptable techniques based upon particles’ population in the search space and a great option for designing FIR filter. PSO and its different variants improve the solution characteristic by providing a unique approach for updating the velocity and position of the swarm. An optimized set of filter coefficient is produced by PSO and its variant algorithms which gives the optimized results in passband and stopband. In this research paper, Digital FIR filter is effectively designed by using PSO Algorithm and its two variants ARPSO and CRPSO in MATLAB. The outcomes prove that the filter design technique using CRPSO is better than filter design by PM algorithm. PSO and ARPSO Algorithms in the context of frequency spectrum and RMS error.

Development of a Low-Cost and Effisient ECG devices with IIR Digital Filter Design


 
 
 
 Measurement of biosignals such as electrocardiograph has the interpretation of noise from other signals. The noise can interfere with the measurement of the heart signal and make the measurement inaccurate, so the purpose of this study is to make a 6-Lead Electrocardiogram module with an Arduino-Based Digital Filter. By using a digital filter. The contribution of this research is the use of digital filters to eliminate noise in electrocardiograph signals. This research uses Infinite Impulse Filter digital filters such as Butterworth, Chebyshev I, Chebyshev II, and Elliptic in order 2, 4, 6, 8, and 10. The study was conducted by providing input from the Function Generator on Arduino which has been applied digital filters with Frequency with 0.5Hz – 100Hz cut-off. The instrument is compared with a factory electrocardiograph. Filter measurements using 460 input data. Butterworth filter with the greatest emphasis on order 8 frequency 0.5Hz produces an emphasis of -5.74298158 dB and a frequency of 100Hz produces an emphasis of -5.93529424 dB. The Chebyshev I filter has the greatest emphasis on order 6 frequency 0.5Hz producing an emphasis of -3.27104076 dB and on order 8 frequency 100Hz producing an emphasis of -5.08730424 dB. Chebyshev II filter the biggest emphasis on the order of frequency 0.5Hz produces a suppression of -44,66011104 dB and 80Hz frequency produces a suppression of -37,3653957 dB. Elliptic filters the greatest emphasis on order 6 frequency 0.5Hz produces an emphasis on -1.55429354 dB and 100Hz frequency on order 8 produces an emphasis on -2.2849115 dB. The results showed that what was appropriate with the cut-off frequency was the Butterworth order 8 filter which was suitable for the application of the Electrocardiograph signal filter because it had bandwidth that suppressed the signal outside the cut-off frequency. The results of this study can be implemented on a 6-Lead ECG module to eliminate noise or interference when tapping ECG signals.
 
 
 

Exploring applications of Frozen Newton Method in the design of digital filter

Digital filters are popularly used in digital signal processing. The design of these filters can be done using different methods of which the rectangular window method and Frequency sampling methods are commonly used. Filter design using wavelet coefficients also shows better response. In this paper, we explore the use of the Frozen Newton method in improving the response of the filter designed using these methods. This iterative computing is applied considering the Taylor series expansion of the function up to the first order term called the Jacobian

A Review of Digital FIR Filter Design in Communication Systems

A Review of Digital FIR Filter Design in Communication Systems

On the Design of an Energy Efficient Digital IIR A-Weighting Filter Using Approximate Multiplication.

This paper presents a new A-weighting filter’s design and explores the potential of using approximate multiplication for low-power digital A-weighting filter implementation. It presents a thorough analysis of the effects of approximate multiplication, coefficient quantization, the order of first-order sections in the filter’s cascade, and zero-pole pairings on the frequency response of the digital A-weighting filter. The proposed A-weighting filter was implemented as a sixth-order IIR filter using approximate odd radix-4 multipliers. The proposed filter was synthesized (Verilog to GDS) using the Nangate45 cell library, and MATLAB simulations were performed to verify the designed filter’s magnitude response and performance. Synthesis results indicate that the proposed design achieves nearly 70% reduction in energy (power-delay product) with a negligible deviation of the frequency response from the floating-point implementation. Experiments on acoustic noise suggest that the proposed digital A-weighting filter can be deployed in environmental noise measurement applications without any notable performance degradation.

Design of Evolutionary Adaptive Notch Filter for GPS Anti-Jamming System

GPS signals can be affected easily by interference due to the low power of signals and the long way between the satellites and receivers. Interference cancellation is one of the major challenges in using GPS. One of the most common intentional interferences is Continuous Wave Interference (CWI) jamming and the most popular way to reduce the impact of it on the GPS signal is using an Adaptive Notch Filter (ANF). Two kinds of heuristic Evolutionary Algorithms (EAs) are used to design second-order IIR Evolutionary Adaptive Notch Filter (EANF). The first algorithm is the Genetic Algorithm (GA) and the second one is Particle Swarm Optimization (PSO) algorithm. EAs are used to find answers to the problems in which there is no specific solution, and this is exactly what is needed to fix the digital filter design problems. NF is implemented in FPGA hardware according to the obtained filter coefficients. Finally, the efficiency of the proposed methods is compared with similar methods in terms of different evaluation metrics. The simulation results show about 12% SNR improvement by using GA and 97% RMS improvement by using the PSO method for higher than 50-dB JSRs.

An Optimal Digital Filtering Technique for Incremental Delta-Sigma ADCs Using Passive Integrators

This paper presents an optimal digital filtering technique to enhance the resolution of incremental delta-sigma modulators (incremental DSMs, IDSMs) using a low-power passive integrator. We first describe a link between a passive integrator and its impact on the output of the IDSM. We then show that the optimal digital filter design can be cast as a convex optimization problem, which can be efficiently solved. As a test vehicle of the proposed technique, we use a behavioral 2nd-order IDSM model that captures critical non-idealities of the integrator, such as gain compression and output saturation. The effectiveness of the presented technique is verified using extensive simulations. The result shows that the presented filtering technique improves signal-to-noise and distortion ratio (SNDR) by 15 dB–20 dB, achieving SNDR over 90 dB when the oversampling ratio (OSR) = 256, and this corresponds to best-in-class performance when compared to previously published DSM designs using passive integrators.

SChoA: a newly fusion of sine and cosine with chimp optimization algorithm for HLS of datapaths in digital filters and engineering applications

The Chimp optimization algorithm (ChoA) inspired by the individual intelligence and sexual motivation of chimps in their group hunting, which is separate from the another social predators. Generally, it is developed for trapping in local optima on the complex functions and alleviate the slow convergence speed. This algorithm has been widely applied to find the best optima solutions of complex global optimization tasks due to its simplicity and inexpensive computational overhead. Nevertheless, premature convergence is easily trapped in the local optimum solution during search process and is ineffective in balancing exploitation and exploration. In this paper, we have developed a modified novel nature inspired optimizer algorithm based on the sine–cosine functions; it is called as sine–cosine chimp optimization algorithm (SChoA). During this research, the sine–cosine functions have been applied to update the equations of chimps during the search process for reducing the several drawbacks of the ChoA algorithm such as slow convergence rate, locating local minima rather than global minima, and low balance amid exploitation and exploration. Experimental solutions based on 23-standard benchmark and 06 engineering functions such as welded beam, tension/compression spring, pressure vessel, multiple disk clutch brake, planetary gear train and digital filters design, etc. demonstrate the robustness, effectiveness, efficiency, and convergence speed of the proposed algorithm in comparison with others.

A Clustering-Based Approach for Designing Low Complexity FIR Filters

Low power requirements, real-time constraints and big data applications present several challenges to digital signal processing (DSP) that span multiple domains including filtering and frequency analysis. Design of digital filters that can efficiently process signals with low computational complexity is desirable and requires innovative approaches. In this paper, we present an efficient two-step design methodology to design low complexity finite-impulse response (FIR) filters. In the first step, the filter design is formulated as an optimization problem to find the minimum number of coefficients, based on K-means clustering with a Euclidean distance metric. In the second step, a mapping approach is proposed to compensate for the mean square error (MSE) that results from the clustering. We compare the proposed method with three different methods from the literature to demonstrate its effectiveness in terms of computational complexity without compromising the filtering performance.

Joint Analog Beam Selection and Digital Beamforming in Millimeter Wave Cell-Free Massive MIMO Systems

Cell-free massive MIMO systems consist of many distributed access points with simple components that jointly serve the users. In millimeter wave bands, only a limited set of predetermined beams can be supported. In a network that consolidates these technologies, downlink analog beam selection stands as a challenging task for the network sum-rate maximization. Low-cost digital filters can improve the network sum-rate further. In this work, we propose low-cost joint designs of analog beam selection and digital filters. The proposed joint designs achieve significantly higher sum-rates than the disjoint design benchmark. Supervised machine learning (ML) algorithms can efficiently approximate the input-output mapping functions of the beam selection decisions of the joint designs with low computational complexities. Since the training of ML algorithms is performed off-line, we propose a well-constructed joint design that combines multiple initializations, iterations, and selection features, as well as beam conflict control, i.e., the same beam cannot be used for multiple users. The numerical results indicate that ML algorithms can retain 99-100% of the original sum-rate results achieved by the proposed well-constructed designs.

Digital Moving Average Filter Application for Echo Signals and Temperature

In this work, we propose a digital filter design, namely moving average filter (MAF) to be implemented on echo signal and temperature data. The echo signal data is obtained from the ultrasonic transducer, while the temperature data is obtained from the PI controller. The implementation of the moving average filter on the echo signal data will compare the second-order MAF and the fourth-order MAF. The results of the test show that the use of a digital filter makes the data smoother when compared to unfiltered data. Furthermore, the comparison of orders on the MAF filter has an impact on the filter response getting closer to the ideal characteristics if using a higher order.

Efficient Filter Generation Based on Particle Swarm Optimization Algorithm

The evaluation of Hankel integration is an important part in the interpretation of electromagnetic (EM) data, especially in physical and geophysical applications. The digital linear filter (DLF) method is commonly applied. For an optimal digital filter design based on matrix inversion, it requires optimization over the model space of the spacing and shift. This is typically obtained by a grid search algorithm on gradually refined grids. In this paper, we apply a particle swarm algorithm to optimize the spacing and shift in the model space. In this algorithm, we use a group of particles to search the model space and do not have to grid the model space sequentially to finer meshes. It has been applied to search the optimal spacing and shift for analytical function pairs, indicating a fast convergence. The performance of the obtained 201-point filter is examined and compared with other published filters based on analytic function pairs and controlled source electromagnetic (CSEM) applications. The results indicate that the proposed 201-point filters have a good numerical performance in terms of accuracy over a large offset range.

The Design and Analysis of Single-bit Ternary Band-pass Digital Filter: Design and Analysis of Single-bit Ternary Band-pass Digital Filter

Recently, various general purpose sigma-delta modulation based general purpose DSP algorithms have been reported that possess simpler multiplier complexity, lower power consumption and less chip area features .Here in exploration, our goal is to carry on designing a ternary-bit DSP algorithm in which significant design element is a sigma delta modulator. The formation sigma - delta (SDM) has an amount of very pleasant and attractive possessions and inborn linearity by reason of which extensively consumed in communication systems. Signal is sampled more than that of Nyquist rate commonly word used oversampling and classically have a very short word length (i-e one-bit, binary or ternary) in sigma delta modulation technique. In this paper the design and simulation of ternary Band pass digital filter using sigma-delta modulation done in Mat-lab at different over-sampling ratio and compare it to multi-bit Band pass digital filter.

Implementation of digital IIR filter design based on field programmable gate array

Abstract Programmable Gate Array (FPGA) software is widely used in digital signal processing (DSP), and DSP algorithms are used in many fields, such as voice signal processing, audio signal processing, picture processing, information systems, system control, etc. Using digital filters as an example, this article uses these three methods to apply filter algorithms and detail the design steps and final validation of the simulation. Based on the recently published low-level parallel filter FIR structure, this document proposes a new design to reduce device complexity. A large number of devices can be stored with the new system. For example, for FIR 576 click filters, when the level of parallelism changes from 12 to 72, the new system can double from 1755 to 3375 at the cost of 21 to 4658 additions and delay elements 1516 to 4749, respectively. This algorithm not only reduces the complexity of computing, but also partially maintains the multiplier aggregation structure, which leads to efficient implementation. This article presents hybrid programming methods that use VB and Matlab to design digital filters.