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Genetic Algorithm For Designing QMF Banks and Its Application In Speech Compression Using Wavelets
Author(s) -
Noureddine Aloui,
Ben Nasr Mohamed,
Adnane Chérif
Publication year - 2013
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2013.06.01
Subject(s) - watermark , digital watermarking , payload (computing) , computer science , scheme (mathematics) , image (mathematics) , embedding , artificial intelligence , pixel , algorithm , authentication (law) , image quality , computer vision , computer security , mathematics , mathematical analysis , network packet
In this paper, real-coded genetic algorithm (GA) is used for designing two-channel quadrature mirror filter (QMF) banks based on the Kaiser Window. The shape of the Kaiser window and the cutoff frequency of the prototype filter are optimized using a simple GA. The optimized QMF banks are exploited as mother wavelets for speech compression based on discret wavelet transform (DWT). The simulation results show the efficiency of the GA for designing QMF banks using adjustable windows length and especially for optimizing wavelet filters used in speech compression based on wavelets. In addition, a comparative of performance of the developed wavelets filters using GA and others known wavelets is made in term of objective criteria (CR, SNR, PSNR, and NRMSE). The simulation results show that the optimized wavelets filters outperform others wavelets already exist used for speech compression

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