Modified second-order nonlinear infinite impulse response (IIR) filter for equalizing frequency response and compensating nonlinear distortions of electrodynamic loudspeaker

In adaptive control applications for noise and vibration, finite ımpulse response (FIR) or ınfinite ımpulse response (IIR) filter structures are used for online adaptation of the controller parameters. IIR filters offer the advantage of representing dynamics of the controller with smaller number of filter parameters than with FIR filters. However, the possibility of instability and convergence to suboptimal solutions are the main drawbacks of such controllers. An IIR filtering-based Steiglitz–McBride (SM) algorithm offers nearly-optimal solutions. However, real-time implementation of the SM algorithm has never been explored and application of the algorithm is limited to numerical studies for active vibration control. Furthermore, the prefiltering procedure of the SM increases the computational complexity of the algorithm in comparison to other IIR filtering-based algorithms. Based on the lack of studies about the SM in the literature, an SM time-domain algorithm for AVC was implemented both numerically and experimentally in this study. A methodology that integrates frequency domain IIR filtering techniques with the classic SM time-domain algorithm is proposed to decrease the computational complexity. Results of the proposed approach are compared with the classical SM algorithm. Both SM and the proposed approach offer multimodal vibration suppression and it is possible to predict the performance of the controller via simulations. The proposed hybrid approach ensures similar vibration suppression performance compared to the classical SM and offers computational advantage as the number of control filter parameters increases.

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FPGA-based Implementation of IIR Filter for Real-Time Noise Reduction in Signal

Journal of Natural Sciences and Engineering ◽

10.14706/jonsae2021316 ◽

2021 ◽

Vol 3 (1) ◽

Author(s):

Aladin Kapić ◽

Rijad Sarić ◽

Slobodan Lubura ◽

Dejan Jokić

Keyword(s):

Transfer Function ◽

Impulse Response ◽

Discrete Time ◽

Time Domain ◽

Digital Filters ◽

Finite Impulse Response ◽

Infinite Impulse Response ◽

Main Role ◽

Digital Implementation ◽

Iir Filter

Filtering of unwanted frequencies represents the main aspect of digital signal processing (DSP) in any modern communication system. The main role of the filter is to perform attenuation of certain frequencies and pass only frequencies of interest. In a DSP system, sampled or discrete-time signals are processed by digital filters using different mathematical operations. Digital filters are commonly categorized as Finite Impulse Response (FIR) and Infinite Impulse Response (IIR). This research focuses on the full VHDL implementation of digital second-order lowpass IIR filter for reducing the noisy frequencies on the FPGA board. The initial step is to determine, from continuous time domain function, the transfer function in the complex {s} domain, then map transfer function in complex {z} domain and finally calculate the difference equation in discrete-time domain of the system with adequate coefficients. Prior to the FPGA implementation, the IIR filter is tested in MATLAB using a signal with mixed frequencies and signal with randomly generated noise. The digital implementation is completed by using fixed-point binary vectors and clocked processes.

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Comparison of Motion Artefact Reduction Methods and the Implementation of Adaptive Motion Artefact Reduction in Wearable Electrocardiogram Monitoring

Sensors ◽

10.3390/s20051468 ◽

2020 ◽

Vol 20 (5) ◽

pp. 1468

Author(s):

Xiang An ◽

George K. Stylios

Keyword(s):

Impulse Response ◽

Adaptive Filter ◽

Finite Impulse Response ◽

Median Filter ◽

Infinite Impulse Response ◽

Ecg Signal ◽

Motion Artefact ◽

Iir Filter ◽

Adaptive Motion ◽

Artefact Reduction

A motion artefact is a kind of noise that exists widely in wearable electrocardiogram (ECG) monitoring. Reducing motion artefact is challenging in ECG signal preprocessing because the spectrum of motion artefact usually overlaps with the very important spectral components of the ECG signal. In this paper, the performance of the finite impulse response (FIR) filter, infinite impulse response (IIR) filter, moving average filter, moving median filter, wavelet transform, empirical mode decomposition, and adaptive filter in motion artefact reduction is studied and compared. The results of this study demonstrate that the adaptive filter performs better than other denoising methods, especially in dealing with the abnormal ECG signal which is measured from a patient with heart disease. In the implementation of adaptive motion artefact reduction, the results show that the use of the impedance pneumography signal as the reference input signal for the adaptive filter can effectively reduce the motion artefact in the ECG signal.

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Design of One-Dimensional Linear Phase Digital IIR Filters Using Orthogonal Polynomials

ISRN Signal Processing ◽

10.5402/2012/870276 ◽

2012 ◽

Vol 2012 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Vinay Kumar ◽

Sunil Bhooshan

Keyword(s):

Orthogonal Polynomials ◽

Impulse Response ◽

Phase 1 ◽

Infinite Impulse Response ◽

Linear Phase ◽

One Dimensional ◽

Iir Filters ◽

Iir Filter ◽

Amplitude Characteristics ◽

Zeros And Poles

In the present paper, we discuss a method to design a linear phase 1-dimensional Infinite Impulse Response (IIR) filter using orthogonal polynomials. The filter is designed using a set of object functions. These object functions are realized using a set of orthogonal polynomials. The method includes placement of zeros and poles in such a way that the amplitude characteristics are not changed while we change the phase characteristics of the resulting IIR filter.

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On Minimal Second-order IIR Bandpass Filters with Constrained Poles and Zeros

Journal of Engineering and Technological Sciences ◽

10.5614/j.eng.technol.sci.2021.53.4.1 ◽

2021 ◽

Vol 53 (4) ◽

pp. 210401

Author(s):

Endra Joelianto

Keyword(s):

Impulse Response ◽

Bandpass Filter ◽

Bandpass Filters ◽

Second Order ◽

Infinite Impulse Response ◽

Frequency Range ◽

Notch Filters ◽

Filter Structure ◽

Poles And Zeros ◽

The Relationship

In this paper, several forms of infinite impulse response (IIR) bandpass filters with constrained poles and zeros are presented and compared. The comparison includes the filter structure, the frequency ranges and a number of controlled parameters that affect computational efforts. Using the relationship between bandpass and notch filters, the two presented filters were originally developed for notch filters. This paper also proposes a second-order IIR bandpass filter structure that constrains poles and zeros and can be used as a minimal parameter adaptive digital second-order filter. The proposed filter has a wider frequency range and more flexibility in the range values of the adaptation parameters.

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Research of Sea Clutter Suppression Algorithm Based on GPU

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.239-240.1194 ◽

2012 ◽

Vol 239-240 ◽

pp. 1194-1201

Author(s):

Yan Guo ◽

Shi Dan Li ◽

De Sheng Wang

Keyword(s):

Impulse Response ◽

Finite Impulse Response ◽

Graphics Processing Unit ◽

Main Idea ◽

Fir Filter ◽

Infinite Impulse Response ◽

Processing Unit ◽

Clutter Suppression ◽

Sea Clutter ◽

Iir Filter

This paper presents an algorithm of sea clutter suppression using graphics processing unit (GPU) to meet the real-time requirement in the general radar terminal system. The main idea is to convert an infinite impulse response (IIR) filter to a finite impulse response (FIR) filter, which is suitable for the parallelization processing of GPU. Finally, the converted FIR filter algorithm is implemented on the GPU efficiently, achieving a speed approximately twice as fast as that of the previous IIR filter algorithm implemented on the CPU.

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A Phasor Measurement Unit Algorithm Using IIR Filters for FPGA Implementation

Electronics ◽

10.3390/electronics8121523 ◽

2019 ◽

Vol 8 (12) ◽

pp. 1523

Author(s):

Cornelis Jan Kikkert

Keyword(s):

Impulse Response ◽

Finite Impulse Response ◽

Block Diagram ◽

Rate Of Change ◽

Measurement Unit ◽

Infinite Impulse Response ◽

Iir Filters ◽

Iir Filter ◽

Phasor Measurement ◽

Ieee Standard

Phasor measurement units (PMU) are increasingly used in electrical power transmission networks, to maintain stability and protect the network. PMUs accurately measure voltage, phase, frequency, and rate of change of frequency (ROCOF). For reliability, it is desirable to implement a PMU using an FPGA. This paper describes a novel algorithm, suited to implementation in an FPGA and based on a simple PMU block diagram. A description of its realization using low hardware complexity infinite impulse response (IIR) filters is given. The IEC/IEEE standard 60255-118-1:2018 Part 118-1: Synchrophasor measurements for power systems, describes “reference” Finite Impulse Response (FIR) filters for implementing PMU hardware. At the 10 kHz sampling frequency used for our implementation, each “reference” FIR filter requires 100 multipliers, while an 8th order IIR filter only requires 12 multipliers. This paper compares the performance of different order IIR filter-based PMUs with the performance of the same PMU algorithm using the IEC/IEEE FIR reference filter. The IIR-based PMU easily satisfies all the requirements of IEC/IEEE standard and has a much better out of band signal rejection performance than a FIR-based PMU. Steady state errors for a rated voltage ± 10% and a rated frequency ± 5 Hz are < 0.000001% for total vector error (TVE) and < 1 µHz for frequency, with a latency of two mains cycles.

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