NDLI: Nonlinear quantization effects in the frequency domain complex scalar LMS adaptive algorithm

Content Provider	IEEE Xplore Digital Library
Author	Sherwood, D. Bershad, N.
Copyright Year	1974
Abstract	Nonlinear quantization effects in the frequency domain complex scalar LMS adaptive algorithm are analyzed by using conditional expectations. The probability density function of the quantizer input, conditioned on the weight, is derived. The density is applied to finding the conditional characteristic function and the Mth conditional moment at the quantizer output. The first and second conditional moments of the quantizer output are used to derive difference equations that approximate the dynamical behavior of the first and second weight moments. These difference equations are solved numerically and compare favorably to simulation results. A model of the quantizer as an additive noise source is of no analytical value since the quantizatian noise has negligible effect on the mean square error when the model is valid. Finally, a design approach is proposed for selecting the number of bits in the weight accumulator. The moment equations are also used to determine the algorithm mean square error for different quantizer step sizes and the optimum algorithm step size μ when a fixed amount of input data is available for adaptation.
Starting Page	140
Ending Page	151
Page Count	12
File Size	1064837
File Format	PDF
ISSN	00963518
Volume Number	34
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1986-02-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Quantization Frequency domain analysis Least squares approximation Adaptive algorithm Difference equations Additive noise Mean square error methods Algorithm design and analysis Probability density function Differential equations
Content Type	Text
Resource Type	Article
Subject	Signal Processing

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