Referenced Items are not available for this document.
The effects of quantization in an least-mean-square (LMS)-Newton adaptive filtering algorithm are investigated. The algorithm considered uses an optimum convergence factor that forces the output a posteriori error to become zero in each iteration. The propagation of errors due to quantization in the internal variables of the algorithm is investigated, and a closed-form formula for the excess mean square error due to quantization is derived. Fixed-point arithmetic is assumed throughout. Several simulations confirm the accuracy of the formulas presented
Published in:
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Date of Conference: 3-6 May 1993
- Page(s):
- 870 - 873 vol.1
- Meeting Date :
- 03 May 1993-06 May 1993
- Print ISBN:
- 0-7803-1281-3
- INSPEC Accession Number:
- 4991322
- Conference Location :
- Chicago, IL
- Digital Object Identifier :
- 10.1109/ISCAS.1993.393862
- Product Type:
- Conference Publications
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