Details Details PDF BIBTEX RIS Title Improving energy compaction of a wavelet transform using genetic algorithm and fast neural network Journal title Archives of Control Sciences Yearbook 2010 Issue No 4 Authors Stolarek, Jan Divisions of PAS Nauki Techniczne Publisher Committee of Automatic Control and Robotics PAS Date 2010 Identifier DOI: 10.2478/v10170-010-0024-5 ; ISSN 1230-2384 Source Archives of Control Sciences; 2010; No 4 References Beyer H.-G. (2002), Evolution strategies - a comprehensive introduction, Natural Computing, 1, 1, 3. ; Cooklev T. (2006), An efficient architecture for orthogonal wavelet transforms, IEEE Signal Processing Letters, 13, 2. ; Daubechies I. (1992), Ten Lectures on Wavelets, doi.org/10.1137/1.9781611970104 ; Dietl W. (2003), Protection of wavelet-based watermarking systems using filter parametrization, Signal Processing, 83, 10, 2095. ; Hu J. (2002), 2002 Congress on Evolutionary Computation. ; Kowalczuk Z. (2004), Genetic algorithms in multi-objective optimization of detection observers, 511. ; Lang M. (1996), The design of maximally smooth wavelets, null, 3, 1463. ; Lipiński P. (2008), On synthesis of 4-tap and 6-tap reversible wavelet filters, Przeglad Elektrotechniczny, 12, 284. ; Mallat S. (2008), A wavelet tour of signal processing. ; Meerwald P. (2001), Watermark security via wavelet filter parametrization, null, 3, 1027. ; Odegard J. (1996), New class of wavelets for signal approximation, null. ; Osowski S. (1994), Signal flow graphs and neural networks, Biological Cybernetics, 70, 4, 387. ; Osowski S. (1996), Application of SFG in learning algorithms of neural networks, null, 75. ; Regensburger G. (2007), Parametrizing compactly supported orthonormal wavelets by discrete moments, Applicable Algebra in Engineering, Communication and Computing, 18, 6, 583. ; Rieder P. (1998), Parameterization of orthogonal wavelet transforms and their implementation, IEEE Trans. on Circuits and Systems II: Analog and Digital Signal Processing, 45, 2, 217. ; Shark L.-K. (2003), Design of optimal shift-invariant orthonormal wavelet filter banks via genetic algorithm, IEEE Trans. on Signal Processing, 83, 2579. ; Stasiak B. (2006), Fast orthogonal neural networks, Lecture Notes in Computer Science, 4029, 142. ; Stolarek J. (2009), Synthesis of a wavelet transform using neural network, null, 26. ; Stolarek J. (2011), On the properties of a lattice structure for a wavelet filter bank implementation: Part 1, J. of Applied Computer Science, 19, 1. ; Stolarek J. (2010), Improving digital watermarking fidelity using fast neural network for adaptive wavelet synthesis, J. of Applied Computer Science, 18, 1, 61. ; Stolarek J. (2009), Image Processing & Communications Challenges. ; Sweldens W. (1995), Wavelet Applications in Signal and Image Processing III, 68, doi.org/10.1117/12.217619 ; Vaidyanathan P. (1988), Lattice structures for optimal design and robust implementation of two-channel perfect-reconstruction QMF banks, IEEE Trans. on Acoustics, Speech and Signal Processing, 36, 1, 81. ; Wei D. (1997), Generalized coiflets: a new family of orthonormal wavelets, null, 2, 1259. ; Yatsymirskyy M. (2009), Lattice structures for synthesis and implementation of wavelet transforms, J. of Applied Computer Science, 17, 1, 133. ; Zou H. (1993), Parametrization of compactly supported orthonormal wavelets, IEEE Trans. on Signal Processing, 41, 3, 1428.