A reduced-complexity quadratic structure for the detection of stochastic signals

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1652_1_online.pdf (1.78 MB)

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https://pubs.aip.org/asa/jasa/article/78/5/1652/628146/A-reduced-complexity-quadratic-structure-for-the

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https://doi.org/10.1121/1.392803
 http://hdl.handle.net/11603/34589

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UMBC Faculty Collection
UMBC Computer Science and Electrical Engineering Department

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Date

1985-11-01

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journal articles
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Citation of Original Publication

Poor, H. Vincent, and Chein-I Chang. “A Reduced-complexity Quadratic Structure for the Detection of Stochastic Signals.” The Journal of the Acoustical Society of America 78, no. 5 (November 1, 1985): 1652–57. https://doi.org/10.1121/1.392803.

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This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Poor, H. Vincent, and Chein-I Chang. “A Reduced-complexity Quadratic Structure for the Detection of Stochastic Signals.” The Journal of the Acoustical Society of America 78, no. 5 (November 1, 1985): 1652–57. https://doi.org/10.1121/1.392803. and may be found at https://pubs.aip.org/asa/jasa/article/78/5/1652/628146/A-reduced-complexity-quadratic-structure-for-the

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Abstract

Quadratic detection of discrete-time stochastic signals in additive stationary Gaussian noise is considered. A banded-quadratic detector structure is introduced to reduce the multiplicative complexity and data storage requirements of the optimum full-quadratic detector, and the optimization of this reduced-complexity structure is studied. The issue of performance versus complexity is explored for the specific problems of detecting wide-sense Markov and triangularly correlated signals in white noise, with the conclusion that performance of the reduced complexity detector can be very close to optimum if an adequate quadratic-form bandwidth is chosen.