An efficient approach to the detection of Bernoulli-Gaussian processes

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1994 (EN)
An efficient approach to the detection of Bernoulli-Gaussian processes (EN)

Kollias, S (EN)
Halkias, C (EN)
Foudopoulos, P (EN)

N/A (EN)

An efficient technique for the detection of a Bernoulli-Gaussian process is proposed in this paper. A new property of the well-known Minimum Variance Deconvolution Filter is derived first, which can feed the detection procedure with reliable estimates of the input process. Based on this derivation, a detection procedure is built, which mainly uses simple detectors, reducing the contribution of more complex ones. The resulting detection procedure performs well and has a very low computational load. Examples are given, which illustrate the theoretical results. (EN)


Parameter estimation (EN)
Optimal systems (EN)
Control system analysis (EN)
Minimum Variance Deconvolution Filter (EN)
Optimal estimation (EN)
Computational complexity (EN)
Parallel processing systems (EN)
Parallel processing (EN)
Kalman filtering (EN)
Mathematical models (EN)
Bernoulli Gaussian processes (EN)
Kalman filters (EN)
Signal detection (EN)

Εθνικό Μετσόβιο Πολυτεχνείο (EL)
National Technical University of Athens (EN)

Automatica (EN)



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