Two High-Performance Adaptive Filter Implementation Schemes Using Distributed Arithmetic

Distributed arithmetic (DA) is performed to design bit-level architectures for vector-vector multiplication with a direct application for the implementation of convolution, which is necessary for digital filters. In this brief, two novel DA-based implementation schemes are proposed for adaptive fini...

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Vydáno v:IEEE transactions on circuits and systems. II, Express briefs Ročník 58; číslo 9; s. 600 - 604
Hlavní autoři: Rui Guo, DeBrunner, L. S.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.09.2011
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Adaptive filter
Adaptive filters
Arithmetic
Circuits
Design engineering
Digital filters
Digital signal processing
distributed arithmetic (DA)
Encoding
Finite impulse response filter
finite-impluse response (FIR)
High speed
least mean square (LMS)
Least squares approximation
lookup table (LUT)
Lookup tables
Mean square values
multiply accumulate (MAC)
offset-binary coding (OBC)
Read only memory
Speech processing
Table lookup
ISSN:1549-7747, 1558-3791
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Shrnutí:Distributed arithmetic (DA) is performed to design bit-level architectures for vector-vector multiplication with a direct application for the implementation of convolution, which is necessary for digital filters. In this brief, two novel DA-based implementation schemes are proposed for adaptive finite-impulse response filters. Different from conventional DA techniques, our proposed schemes use coefficients as addresses to access a series of lookup tables (LUTs) storing sums of delayed and scaled input samples. Two smart LUT updating methods are developed, and least-mean-square adaptation is performed to update the weights and minimize the mean square error between the estimated and desired output. Results show that our two high-performance designs achieve high speed, low computation complexities, and low area cost.
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ISSN:1549-7747
1558-3791
DOI:10.1109/TCSII.2011.2161168