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Showing papers on "Quadrature mirror filter published in 2019"


Proceedings ArticleDOI
01 Sep 2019
TL;DR: A concept of the Crisscross Optimization method for minimizing designing error of two channel linear phase QMF bank in frequency domain is introduced and the simulation results are compared with the modified particle swarm optimization, artificial bee colony, XSG and Levenberg Marquart method.
Abstract: During designing of two channel Quadrature Mirror Filter(QMF) bank, there occurs many errors such as peak reconstruction error, error in pass band, error in stop band, error in transition band and amplitude distortion. There are many meta-heuristic algorithms for the minimization of various errors of two channel QMF banks but they have drawbacks that either their convergence speed is slow or they have poor solution accuracy or premature convergence. In this paper, a concept of the Crisscross Optimization method for minimizing designing error of two channel linear phase QMF bank in frequency domain is introduced. This problem is taken as single objective function. The crisscross optimization algorithm makes use of two important operators that are horizontal crossover (HCX) and vertical crossover (VCX). The HCX operator works by dividing the problem space into simple hypercube with smaller search probability while VCX operator makes a way out for the stagnant dimensions which may be indifferentiable and cause premature convergence. The simulation results are compared with the modified particle swarm optimization, artificial bee colony, XSG and Levenberg Marquart method. From the comparison it is obvious that convergence speed and good solution accuracy.

10 citations


Journal ArticleDOI
TL;DR: In this article, a generalized shearlet construction for arbitrary dimensions and arbitrary scalings for which the filterbank construction ensures the existence of an orthogonal wavelet analysis is presented.

6 citations


Proceedings ArticleDOI
01 Jul 2019
TL;DR: In this paper, two approaches to the construction of scaling functions and wavelets that generate nearly cardinal and nearly symmetric wavelets on the line are presented, one of which casts wavelet construction as an optimization problem by imposing constraints on the integer samples of the scaling function and its associated wavelet and with an objective function that minimizes deviation from cardinality or symmetry.
Abstract: We present two approaches to the construction of scaling functions and wavelets that generate nearly cardinal and nearly symmetric wavelets on the line. The first approach casts wavelet construction as an optimization problem by imposing constraints on the integer samples of the scaling function and its associated wavelet and with an objective function that minimizes deviation from cardinality or symmetry. The second method is an extension of the feasibility approach by Franklin, Hogan, and Tam to allow for symmetry by considering variables generated from uniform samples of the quadrature mirror filter, and is solved via the Douglas-Rachford algorithm.

4 citations


Proceedings ArticleDOI
01 Oct 2019
TL;DR: This paper presents the minor component analysis algorithm for designing 2-channel quadrature mirror filter using the polyphase structure and demonstrates that the exploited neural learning algorithm achieves accurate design performance.
Abstract: Polyphase framework has been found considerable investigation due to its flexibility in filter implementation. This paper presents the minor component analysis algorithm for designing 2-channel quadrature mirror filter using the polyphase structure. The low-pass prototype analysis filter is achieved when the linear neural model reaches convergence. Simulation results demonstrate that the exploited neural learning algorithm achieves accurate design performance.

2 citations


Patent
01 Jan 2019
TL;DR: In this paper, the authors proposed a classification method based on the combination of a quadrature mirror filter group and a convolutional neural network, which can automatically extract a plurality of low probability intercept (LPI) signal characteristics.
Abstract: A modern radar generally uses a low probability intercept (LPI) radar signal to detect a target so that LPI signal classification is needed in radar countermeasures. Currently, a traditional artificial characteristic extraction algorithm is used to classify, and during practical application, the classification correct rate of the algorithm is not ideal. The invention provides a classification method based on the combination of a quadrature mirror filter group and a convolutional neural network. The method comprises the following steps of firstly, carrying out QMFB processing on an interceptedradar signal to obtain radar layered time frequency images; then, based on the novel convolutional neural network, classifying the radar layered time frequency images; and finally, outputting a LPI radar signal classification result. In the invention, based on the convolutional neural network, a plurality of LPI signal characteristics can be automatically extracted, and compared with the traditional algorithm, the method of the invention has improved classification efficiency and an improved identification correct rate.

1 citations


Book ChapterDOI
01 Jan 2019
TL;DR: A novel hybrid algorithm based on Multi-swarm Cooperative Particle Swarm Optimization (MCPSO) and Simulated Annealing (SA) for the design of higher order Quadrature Mirror Filter (QMF) bank is presented.
Abstract: This paper presents a novel hybrid algorithm based on Multi-swarm Cooperative Particle Swarm Optimization (MCPSO) and Simulated Annealing (SA) for the design of higher order Quadrature Mirror Filter (QMF) bank. The optimization of lower order filters can be carried out easily by traditional optimization methods, but these approaches failed to find higher order filter coefficients due to nonlinear and multimodality problem space. Most of the optimization algorithms are easily trapped into local optimum which yields few unwanted characteristics in filter magnitude responses like ripples in transition region, lower stop-band attenuation. The proposed algorithm, named Simulated Annealing-based Multi-swarm Cooperative PSO (SAMCPSO), is presented here to obtain prototype filter that leads to near-perfect reconstruction for both lower and higher dimensional filter banks. Comparison with other existing methods in the literature demonstrates that the proposed algorithm exhibits an average increase of 17.39% in stop-band attenuation and 47.35% reduction in Perfect Reconstruction Error (PRE) of 82-tap filter bank.

1 citations


Proceedings ArticleDOI
01 Jul 2019
TL;DR: This proposed paper presents a design approach for two-channel quadrature mirror filter (QMF) bank using improved artificial bee colony algorithm modified by fine tuning some existing control parameters for lowpass prototype FIR filter design problem.
Abstract: This proposed paper presents a design approach for two-channel quadrature mirror filter (QMF) bank using improved artificial bee colony algorithm. Artificial bee colony algorithm has been modified by fine tuning some existing control parameters. Here QMF bank design is used for a lowpass prototype FIR filter design problem. The objective function is the minimizing of mean square error of magnitude responses between desired and designed low-pass prototype FIR filters. The objective function is minimized by using the modified ABC algorithm yielding improved results. Two design examples are also presented to show the efficiency of the proposed method over the existing methods in the literature. The results of the proposed design approach have also been compared with that of the produced results in the literature.