For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
LMS-Based Algorithms with Multi-Band Decomposition of the Estimation Error Applied to System Identification
Fernando Gil V. RESENDE,Jr Paulo S.R. DINIZ Keiichi TOKUDA Mineo KANEKO Akinori NISHIHARA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1997/08/25
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
adaptive signal processing, fixed and variable step-size LMS algorithms, filter banks, system identification,
Full Text: PDF(629.5KB)>>
A new cost function based on multi-band decomposition of the estimation error and application of a different step-size for each band is used in connection with the least-mean-square criterion to improve the fidelity of estimates as compared to those obtained with conventional least-mean-square adaptive algorithms. The basic new idea is to trade off time and frequency resolutions of the adaptive algorithm along the frequency domain by using different step-sizes in the analysis of distinct frequencies in accordance with the frequency-localized statistical behavior of the imput signal. The mathematical background for a stochatic approach to the multi-band decomposition-based scheme is presented and algorithms with fixed and variable step-sizes are derived. Computer experiments compare the performance of multiband and conventional least-mean-square methods when applied to system identification.