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Joint Optimization of Distributed Broadcast Quantization Systems for Classification

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2 Author(s)
Lexa, Michael A. ; Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX ; Johnson, D.H.

We develop a simulated annealing technique to jointly optimize a distributed quantization structure meant to maximize the asymptotic error exponent of a downstream classifier or detector. This distributed structure sequentially processes an input vector and exploits broadcasts to improve the best possible error exponents. The annealing approach is a robust technique that avoids local maxima and is easily tailored to a broadcast quantizer's structural constraints

Published in:

Data Compression Conference, 2007. DCC '07

Date of Conference:

27-29 March 2007