Conference proceeding
A Cost Function Level Analysis of Autocorrelation Minimization Based Blind Adaptive Channel Shorteners
2008 42ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-4, pp 2193-2197
01 Jan 2008
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper considers a cost function level analysis of the Sum-squared Autocorrelation Minimization (SAM) channel shortening algorithm. We point out that the actual cost the blind adaptive stochastic gradient descent algorithm is minimizing is only indirectly related to the sum squared autocorrelation. We study the asymptotic regimes under which the actual cost yields a reliable surrogate for the sum squared autocorrelation. We investigate the relationship between the minima of the actual cost and sum squared autocorrelation. We also study the upper bound of the approximate cost as a function of the window size used in the approximate autocorrelation calculation.
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3 citations in Scopus
Details
- Title
- A Cost Function Level Analysis of Autocorrelation Minimization Based Blind Adaptive Channel Shorteners
- Creators
- Ciira Wa Maina - Drexel UniversityJohn MacLaren Walsh - Drexel University
- Contributors
- M B Matthews (Editor)
- Publication Details
- 2008 42ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-4, pp 2193-2197
- Series
- Conference Record of the Asilomar Conference on Signals Systems and Computers
- Publisher
- IEEE
- Number of pages
- 5
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000274551001199
- Scopus ID
- 2-s2.0-70349678326
- Other Identifier
- 991019168197004721
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- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Electrical & Electronic
- Telecommunications