scholarly journals A Proportionate Normalized Maximum Correntropy Criterion Algorithm with Correntropy Induced Metric Constraint for Identifying Sparse Systems

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 683 ◽  
Author(s):  
Yingsong Li ◽  
Yanyan Wang ◽  
Laijun Sun
Keyword(s):  
Impulse Response ◽  
Adaptive Filter ◽  
Finite Impulse Response ◽  
Least Mean Square ◽  
Sparse Systems ◽  
Simulation Results ◽  
Maximum Correntropy Criterion ◽  
Non Gaussian ◽  
Fir Systems ◽  
Filter Algorithms

A proportionate-type normalized maximum correntropy criterion (PNMCC) with a correntropy induced metric (CIM) zero attraction terms is presented, whose performance is also discussed for identifying sparse systems. The proposed sparse algorithms utilize the advantage of proportionate schemed adaptive filter, maximum correntropy criterion (MCC) algorithm, and zero attraction theory. The CIM scheme is incorporated into the basic MCC to further utilize the sparsity of inherent sparse systems, resulting in the name of the CIM-PNMCC algorithm. The derivation of the CIM-PNMCC is given. The proposed algorithms are used for evaluating the sparse systems in a non-Gaussian environment and the simulation results show that the expanded normalized maximum correntropy criterion (NMCC) adaptive filter algorithms achieve better performance than those of the squared proportionate algorithms such as proportionate normalized least mean square (PNLMS) algorithm. The proposed algorithm can be used for estimating finite impulse response (FIR) systems with symmetric impulse response to prevent the phase distortion in communication system.

scholarly journals Adaptive Parameter Estimation of IIR System-Based WSN Using Multihop Diffusion in Distributed Approach

2020 ◽  
Vol 14 (4) ◽  
pp. 30-41
Author(s):  
Meera Dash ◽  
Trilochan Panigrahi ◽  
Renu Sharma ◽  
Mihir Narayan Mohanty
Keyword(s):  
Impulse Response ◽  
Sensor Node ◽  
Finite Impulse Response ◽  
Lms Algorithm ◽  
Sensor System ◽  
Superior Performance ◽  
Estimation Accuracy ◽  
Infinite Impulse Response ◽  
Communication Overhead ◽  
Least Mean Square

Distributed estimation of parameters in wireless sensor networks is taken into consideration to reduce the communication overhead of the network which makes the sensor system energy efficient. Most of the distributed approaches in literature, the sensor system is modeled with finite impulse response as it is inherently stable. Whereas in real time applications of WSN like target tracking, fast rerouting requires, infinite impulse response system (IIR) is used to model and that has been chosen in this work. It is assumed that every sensor node is equipped with IIR adaptive system. The diffusion least mean square (DLMS) algorithm is used to estimate the parameters of the IIR system where each node in the network cooperates themselves. In a sparse WSN, the performance of a DLMS algorithm reduces as the degree of the node decreases. In order to increase the estimation accuracy with a smaller number of iterations, the sensor node needs to share their information with more neighbors. This is feasible by communicating each node with multi-hop nodes instead of one-hop only. Therefore the parameters of an IIR system is estimated in distributed sparse sensor network using multihop diffusion LMS algorithm. The simulation results exhibit superior performance of the multihop diffusion LMS over non-cooperative and conventional diffusion algorithms.

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

Sensors ◽  
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.

scholarly journals A Kernel-Width Adaption Diffusion Maximum Correntropy Algorithm

2020 ◽  
Author(s):  
Ying Guo ◽  
Bing Ma ◽  
Yingsong Li
Keyword(s):  
Steady State ◽  
Impulse Noise ◽  
Kernel Width ◽  
Sparse System ◽  
Initial Stage ◽  
Small Kernel ◽  
Sparse Systems ◽  
Simulation Results ◽  
Maximum Correntropy Criterion ◽  
Large Kernel

In this paper, a diffusion maximum correntropy criterion (DMCC) algorithm with adaption kernel width is proposed, denoting as DMCC$_{\rm adapt}$ algorithm, to find out a solution for dynamically choosing the kernel width. The DMCC$_{\rm adapt}$ algorithm chooses small kernel width at initial stage to improve its convergence speed rate, and uses large kernel width at completion stage to reduce its steady-state error. To render the proposed DMCC$_{\rm adapt}$ algorithm suitable for sparse system identifications, the DMCC$_{\rm adapt}$ algorithm based on proportional coefficient adjustment is realized and named as diffusion proportional maximum correntropy criterion (DPMCC$_{\rm adapt}$). The theoretical analysis and simulation results are presented to show that the DPMCC$_{\rm adapt}$ and DMCC$_{\rm adapt}$ algorithms have better convergence than the traditional diffusion AF algorithms under impulse noise and sparse systems.

scholarly journals High Performance Motion Tracking Control for Electronic Manufacturing

2007 ◽  
Vol 129 (6) ◽  
pp. 767-776 ◽  
Author(s):  
Benjamin Potsaid ◽  
John Ting-Yung Wen ◽  
Mark Unrath ◽  
David Watt ◽  
Mehmet Alpay
Keyword(s):  
Motion Control ◽  
Impulse Response ◽  
Finite Impulse Response ◽  
Learning Control ◽  
Iterative Refinement ◽  
Performance Criteria ◽  
Mean Square ◽  
Least Mean Square ◽  
Positioning Systems ◽  
Electronic Manufacturing

Motion control requirements in electronic manufacturing demand both higher speeds and greater precision to accommodate continuously shrinking part/feature sizes and higher densities. However, improving both performance criteria simultaneously is difficult because of resonances that are inherent to the underlying positioning systems. This paper presents an experimental study of a feedforward controller that was designed for a point-to-point motion control system on a modern and state of the art laser processing system for electronics manufacturing. We systematically apply model identification, inverse dynamics control, iterative refinement (to address modeling inaccuracies), and adaptive least mean square to achieve high speed trajectory tracking. The key innovations lie in using the identified model to generate the gradient descent used in the iterative learning control, encoding the result from the learning control in a finite impulse response filter and adapting the finite impulse response coefficients during operation using the least-mean-square update based on position, velocity, and acceleration feedforward signals. Experimental results are provided to show the efficacy of the proposed approach, a variation of which has been implemented on the production machine.

scholarly journals Frequency domain maximum correntropy criterion spline adaptive filtering

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wenyan Guo ◽  
Yongfeng Zhi ◽  
Kai Feng
Keyword(s):  
Frequency Domain ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Adaptive Filters ◽  
Operation Time ◽  
Filtering Algorithm ◽  
Impulsive Noises ◽  
Type Frequency ◽  
Maximum Correntropy Criterion ◽  
Non Gaussian

AbstractA filtering algorithm based on frequency domain spline type, frequency domain spline adaptive filters (FDSAF), effectively reducing the computational complexity of the filter. However, the FDSAF algorithm is unable to suppress non-Gaussian impulsive noises. To suppression non-Gaussian impulsive noises along with having comparable operation time, a maximum correntropy criterion (MCC) based frequency domain spline adaptive filter called frequency domain maximum correntropy criterion spline adaptive filter (FDSAF-MCC) is developed in this paper. Further, the bound on learning rate for convergence of the proposed algorithm is also studied. And through experimental simulations verify the effectiveness of the proposed algorithm in suppressing non-Gaussian impulsive noises. Compared with the existing frequency domain spline adaptive filter, the proposed algorithm has better performance.

scholarly journals Implementasi Filter Finite Impulse Response (FIR) Window Hamming dan Blackman menggunakan DSK TMS320C6713

2018 ◽  
Vol 4 (1) ◽  
pp. 16
Author(s):  
LITA LIDYAWATI ◽  
PAULINE RAHMIATI ◽  
YULI SUNARTI
Keyword(s):  
Impulse Response ◽  
Digital Filter ◽  
Finite Impulse Response ◽  
Sampling Frequency ◽  
Test Results ◽  
Frequency Bandwidth ◽  
Magnitude Response ◽  
Frequency Bands ◽  
Stopband Attenuation ◽  
Simulation Results

ABSTRAKFilter didefinisikan sebagai proses atau rangkaian yang melewatkan pita frekuensi tertentu yang diinginkan dan meredam pita frekuensi lainnya. Salah satu metode perancangan filter digital Finite Impulse Response (FIR) adalah metode windowing. Dalam penelitian ini digunakan jenis window Hamming dan Blackman. Simulasi dilakukan dengan menggunakan software Matlab dengan memasukan frekuensi passband, frekuensi stopband, ripple passband, dan stopband attenuation. Dengan frekuensi sampling sebesar 15000 Hz, frekuensi passband sebesar 3000 Hz, frekuensi stopband sebesar 5000 Hz. Setelah simulasi dilakukan implementasi filter dengan parameter yang sama menggunakan DSK TMS 320C6713 dengan bantuan software CCS. Simulasi dan implementasi dilakukan pada semua band frekuensi. Hasil pengujian terhadap implementasi filter adalah respon magnitude, frekuensi cut-off, bandwidth, dan faktor kualitas dengan hasil simulasi tidak menunjukkan perbedaan yang signifikan.Kata kunci: filter digital, windowing, Hamming, Blackman, frekuensi cut-off.ABSTRACTFilter is defined as a process or series that skip certain desired frequency band and other frequency bands drown. One method of designing a digital filter Finite Impulse Response (FIR) is a windowing method. This study used the type of window Hamming and Blackman. Simulations performed using Matlab software by inserting a frequency passband, stopband frequency, passband ripple, and stopband attenuation. With a sampling frequency of 15,000 Hz, a frequency of 3000 Hz passband, stopband frequency of 5000 Hz. After the simulation is completed, implementation of the filter with the same parameters using TMS 320C6713 DSK with the help of software CCS. Simulation and implmentasi performed on all frequency bands. The test results of the implementation of the filter is the Magnitude response, the cut-off frequency, bandwidth, and quality factor with simulation results showed no significant difference.Keywords: digital filter, windowing, Hamming, Blackman, cut-off frequency.

Design of New Reconfigurable Architecture for Implementing a Least Mean Square Finite Impulse Response Filter Using Borrow Select Subtraction (BSLS)

2020 ◽  
Vol 17 (4) ◽  
pp. 1943-1948
Author(s):  
P. Mukunthan ◽  
N. C. Sendhilkumar ◽  
R. Pitchai
Keyword(s):  
Adaptive Filter ◽  
Finite Impulse Response ◽  
Full Adder ◽  
Fir Filter ◽  
Reconfigurable Architecture ◽  
Mean Square ◽  
Least Mean Square ◽  
Lms Filter ◽  
Ripple Carry Adder ◽  
Filter Architecture

A design of reconfigurable architecture of FIR filter has been implemented using a Least Mean Square (LMS) adaptive filter. LMS adaptive filter is mainly sued for reducing the coefficients of the filter. Generally, a LMS filter contains normal adder, subtractor, mixer and a delay part. Most of the concepts deal with an adder namely Full Adder (FA), Ripple Carry Adder (RCA), Carry Select Adder (CSLA), etc., Instead of using CSLA; Borrow Select Subtractor (BSLS) is used in LMS filter architecture. By using BSLA LMS adaptive filter in a reconfigurable FIR filter architecture in the proposed scheme, the area, power and delay will be reduced. The proposed scheme achieves better performance when compared to an existing scheme. The proposed method is implemented in ModelSim tool and efficiency has been calculated by using the device Virtex 6 Low Power in Xilinx ISE Design Suite 12.4.

Vibration Suppression Based on Adaptive Feedforward Control With Infinite Impulse Response Filter

2015 ◽  
Author(s):  
Shiying Zhou ◽  
Masayoshi Tomizuka
Keyword(s):  
Impulse Response ◽  
Vibration Suppression ◽  
Finite Impulse Response ◽  
Feedforward Control ◽  
Vibration Signal ◽  
Infinite Impulse Response ◽  
Least Mean Square ◽  
Parameter Adaptation ◽  
Iir Filter ◽  
Adaptive Feedforward

This paper presents adaptive feedforward control for vibration suppression based on an infinite impulse response (IIR) filter structure. The vibration signal and the output signal are available for the algorithm to adaptively update the parameters of the vibration transmission path (VTP) dynamics. Two designs for parameter adaptation are proposed. They provide different methods to get the necessary signals for parameter adaptation of the IIR filter which is different from the conventional finite impulse response (FIR) filter adaptation design. Performance of the proposed designs is compared with the conventional Filtered-x Least Mean Square (FxLMS) method on a hard disk drive (HDD) benchmark problem. The simulation results show that the proposed designs have smaller 3σ value and peak to peak value at steady state.

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