Evolutionary Design of Digital Filters With Application to Subband Coding and Data Transmission

In this paper, two evolutionary programming (EP) algorithms (classical EP and fast EP) are applied to design prototype lowpass Finite Impulse Response filters for use in a modulated filterbank. The chosen filter design technique is based on frequency-sampling (where the Fourier transform magnitudes of the filter are the objective variables). Design is simplified by constraining most of these values, leaving only a small number of values in the filter transition band to be optimized. The EP algorithms were used to determine the optimum values for this subset of values. Since there is an additional monotonic constraint on the transition band values, a modification to the EP algorithms was developed called variable limits evolutionary programming. Results indicate that a) both EP algorithms were insensitive to initial conditions, and reliably found the minimum values of the chosen objective functions, and b) the designed prototype filters are suitable to obtain near-perfect reconstruction filter banks, offering quality parameters comparable or better than systems obtained using other techniques

[1]  David B. Fogel,et al.  Evolutionary Computation: Towards a New Philosophy of Machine Intelligence , 1995 .

[2]  Shahriar Mirabbasi,et al.  Overlapped complex-modulated transmultiplexer filters with simplified design and superior stopbands , 2003, IEEE Trans. Circuits Syst. II Express Briefs.

[3]  Behrouz Farhang-Boroujeny,et al.  Analysis of post-combiner equalizers in cosine-modulated filterbank-based transmultiplexer systems , 2003, IEEE Trans. Signal Process..

[4]  Masayuki Kawamata,et al.  Synthesis of low-sensitivity second-order digital filters using genetic programming with automatically defined functions , 2000, IEEE Signal Processing Letters.

[5]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[6]  Masao Iwamatsu,et al.  Generalized evolutionary programming with Lévy-type mutation , 2002 .

[7]  Safieddin Safavi-Naeini,et al.  A hybrid evolutionary programming method for circuit optimization , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.

[8]  Markku Renfors,et al.  Exponentially-modulated filter bank-based transmultiplexer , 2003, Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03..

[9]  Fernando Cruz-Roldán,et al.  Frequency sampling design of prototype filters for nearly perfect reconstruction cosine-modulated filter banks , 2004, IEEE Signal Processing Letters.

[10]  P. K. Chattopadhyay,et al.  Fast Evolutionary Progranuning Techniques for Short-Term Hydrothermal Scheduling , 2002, IEEE Power Engineering Review.

[11]  Nurhan Karaboga,et al.  Artificial immune algorithm for IIR filter design , 2005, Eng. Appl. Artif. Intell..

[12]  Xin Yao,et al.  Evolutionary programming using mutations based on the Levy probability distribution , 2004, IEEE Transactions on Evolutionary Computation.

[13]  S.-L. Lu,et al.  Application of DFT filter bank to power frequency harmonic measurement , 2005 .

[14]  Tanja Karp,et al.  Modified DFT filter banks with perfect reconstruction , 1999 .

[15]  Masayuki Kawamata,et al.  Synthesis of low-sensitivity second-order digital filters using genetic programming with automatically defined functions , 2000 .

[16]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .

[17]  Behrouz Farhang-Boroujeny,et al.  Multicarrier modulation with blind detection capability using cosine modulated filter banks , 2003, IEEE Trans. Commun..

[18]  Ali N. Akansu,et al.  Wavelet, Subband, and Block Transforms in Communications and Multimedia , 1999 .

[19]  Sanjit K. Mitra,et al.  A simple method for designing high-quality prototype filters for M-band pseudo QMF banks , 1995, IEEE Trans. Signal Process..

[20]  L. Rabiner,et al.  An approach to the approximation problem for nonrecursive digital filters , 1970 .

[21]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[22]  Xin Yao,et al.  Digital filter design using multiple pareto fronts , 2004, Soft Comput..

[23]  Thomas Bäck,et al.  Evolutionary computation: Toward a new philosophy of machine intelligence , 1997, Complex..

[24]  Hean-Teik Chuah,et al.  Multiuser detection for DS-CDMA systems using evolutionary programming , 2003, IEEE Communications Letters.

[25]  M. Kawamata,et al.  Evolutionary synthesis of digital filter structures using genetic programming , 2003, IEEE Trans. Circuits Syst. II Express Briefs.

[26]  James P. Reilly,et al.  Efficient design of oversampled NPR GDFT filterbanks , 2004, IEEE Transactions on Signal Processing.

[27]  N. Karaboga,et al.  Design of minimum phase digital IIR filters by using genetic algorithm , 2004, Proceedings of the 6th Nordic Signal Processing Symposium, 2004. NORSIG 2004..

[28]  Hui Zhao,et al.  A fast evolutionary programming for adaptive FIR filter , 2004, 2004 International Conference on Communications, Circuits and Systems (IEEE Cat. No.04EX914).

[29]  David B. Fogel,et al.  Using evolutionary programming to schedule tasks on a suite of heterogeneous computers , 1996, Comput. Oper. Res..

[30]  Martin Schneider,et al.  Design of Digital Filters with Evolutionary Algorithms , 1993 .

[31]  Frank Sjöberg,et al.  Digital RFI suppression in DMT-based VDSL systems , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[32]  See-May Phoong,et al.  DFT-modulated filterbank transceivers for multipath fading channels , 2005, IEEE Transactions on Signal Processing.

[33]  Markku Renfors,et al.  Filter-Bank-Based Narrowband Interference Detection and Suppression in Spread Spectrum Systems , 2002, EURASIP J. Adv. Signal Process..

[34]  P. K. Chattopadhyay,et al.  Fast evolutionary programming techniques for short-term hydrothermal scheduling , 2003 .

[35]  James Smith,et al.  A tutorial for competent memetic algorithms: model, taxonomy, and design issues , 2005, IEEE Transactions on Evolutionary Computation.

[36]  A. A. El-Keib,et al.  Maintenance scheduling of generation and transmission systems using fuzzy evolutionary programming , 2003 .

[37]  Manuel Blanco-Velasco,et al.  Frequency sampling design of arbitrary-length filters for filter banks and Discrete Subband Multitone transceivers , 2005, 2005 13th European Signal Processing Conference.

[38]  David B. Fogel,et al.  An introduction to simulated evolutionary optimization , 1994, IEEE Trans. Neural Networks.

[39]  Loi Lei Lai,et al.  Determination of operational parameters of electrical machines using evolutionary programming , 1995 .

[40]  Tong Heng Lee,et al.  Evolutionary computing for knowledge discovery in medical diagnosis , 2003, Artif. Intell. Medicine.

[41]  Eiichi Tanaka,et al.  An Evolutionary Programming Solution to the Unit Commitment Problem , 1997 .

[42]  Seppo J. Ovaska,et al.  Evolutionary-programming-based optimization of reduced-rank adaptive filters for reference generation in active power filters , 2004, IEEE Transactions on Industrial Electronics.

[43]  Aristotelis Mantoglou,et al.  Management of coastal aquifers based on nonlinear optimization and evolutionary algorithms , 2004 .

[44]  Paul W. Fieguth,et al.  Forest structure optimization using evolutionary programming and landscape ecology metrics , 2005, Eur. J. Oper. Res..

[45]  Robert Bregovic,et al.  Multirate Systems and Filter Banks , 2002 .

[46]  Truong Q. Nguyen,et al.  A general formulation of modulated filter banks , 1999, IEEE Trans. Signal Process..

[47]  Winfried Vonau,et al.  Evolutionary computer programming of protein folding and structure predictions. , 2004, Journal of theoretical biology.

[48]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[49]  P. P. Vaidyanathan,et al.  A Kaiser window approach for the design of prototype filters of cosine modulated filterbanks , 1998, IEEE Signal Processing Letters.