Journal ArticleDOI
Performance analysis of frequency-domain block LMS adaptive digital filters
Jae Chon Lee,Chong Kwan Un +1 more
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TLDR
In this article, the performance of the frequency-domain block least-mean-square (FBLMS) adaptive digital filters, whose filter weights are updated efficiently using the fast Fourier transform, is investigated.Abstract:
The performance of the frequency-domain block least-mean-square (FBLMS) adaptive digital filters, whose filter weights are updated efficiently using the fast Fourier transform, is investigated. In particular, the convergence of the unconstrained FBLMS algorithm with reduced complexity, which is obtained by removing the constraint that has been known to be required in adjusting the frequency-domain weights based on overlap-save sectioning, is analyzed. The performance of the self-orthogonalizing FBLMS algorithm with improved convergence speed, in which different convergence factors normalized by frequency-domain power estimates are used for different frequency components of the weights, is also studied. >read more
Citations
More filters
Journal ArticleDOI
Frequency-domain and multirate adaptive filtering
TL;DR: An overview is presented of several frequency-domain adaptive filters that efficiently process discrete-time signals using block and multirate filtering techniques, including convergence properties and computational complexities of the adaptive algorithms and the effects of circular convolution and aliasing on the converged filter coefficients.
Journal ArticleDOI
Efficient least squares adaptive algorithms for FIR transversal filtering
TL;DR: A unified view of algorithms for adaptive transversal FIR filtering and system identification has been presented, and the LMS algorithm and its offspring have been presented and interpreted as stochastic approximations of iterative deterministic steepest descent optimization schemes.
Journal ArticleDOI
Performance analysis of LMS adaptive prediction filters
TL;DR: It is shown that there is a nonlinear degradation in the signal processing gain as a function of the input SNR that results from the statistical properties of the adaptive filter weights.
Journal ArticleDOI
Adaptive filtering in subbands using a weighted criterion
M. de Courville,Pierre Duhamel +1 more
TL;DR: An adaptive algorithm compatible with the use of rectangular orthogonal transforms is proposed, thus allowing better tradeoffs between algorithm improvement, arithmetic complexity, and input/output delay, and leading to improvements in the convergence rate compared with both LMS and classical frequency domain algorithms.
Journal ArticleDOI
The generalized multidelay adaptive filter: structure and convergence analysis
TL;DR: The authors present a comprehensive analysis of the performance of this new frequency-domain LMS adaptive scheme, the generalized multidelay filter (GMDF), and provide insight into the influence of impulse response segmentation on the behavior of the adaptive algorithm.
References
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Book
Adaptive Signal Processing
Bernard Widrow,Samuel D. Stearns +1 more
TL;DR: This chapter discusses Adaptive Arrays and Adaptive Beamforming, as well as other Adaptive Algorithms and Structures, and discusses the Z-Transform in Adaptive Signal Processing.
Book ChapterDOI
Stationary and nonstationary learning characteristics of the LMS adaptive filter
TL;DR: It is shown that for stationary inputs the LMS adaptive algorithm, based on the method of steepest descent, approaches the theoretical limit of efficiency in terms of misadjustment and speed of adaptation when the eigenvalues of the input correlation matrix are equal or close in value.
Journal ArticleDOI
Transform domain LMS algorithm
TL;DR: In this article, the concept of transform domain adaptive filtering is introduced and the relationship between several existing frequency-domain adaptive filtering algorithms is established, and applications of the discrete Fourier transform (DFT) and the discrete cosine transform (DCT) domain adaptive filter algorithms in the areas of speech processing and adaptive line enhancers are discussed.
Journal ArticleDOI
Fast implementations of LMS adaptive filters
TL;DR: In this paper, a frequency domain implementation of the LMS adaptive transversal filter is proposed, which requires less computation than the conventional LMS filter when the filter length equals or exceeds 64 sample points.
Journal ArticleDOI
Adaptive filtering in the frequency domain
TL;DR: Adaptive filtering in the frequency domain can be accomplished by Fourier transformation of the input signal and independent weighting of the contents of each frequency bin this article, which performs similarly to a conventional adaptive transversal filter but promises a significant reduction in computation when the number of weights equals or exceeds 16.