A decentralized estimation scheme with two sensors, where data are remotely encoded by scalar quantizer to fulfill capacity constraints of channels conveying information to a central estimator, has been investigated. The quantizers are to operate separately, but a joint model of observations, allowing for spatially correlated data, may be taken into account at the design stage. A design algorithm has been derived. For a linear Gaussian observation model the limit performance of any encoding-decoding scheme has been obtained in terms of an upper bound to the rate-distortion function. Under various combinations of per-channel signal-to-noise ratios and spatial correlation coefficients, quantizers designed by the proposed algorithm nearly achieve such limit performance.

Quantization for decentralized estimation from correlated data

DI BISCEGLIE M;
1990-01-01

Abstract

A decentralized estimation scheme with two sensors, where data are remotely encoded by scalar quantizer to fulfill capacity constraints of channels conveying information to a central estimator, has been investigated. The quantizers are to operate separately, but a joint model of observations, allowing for spatially correlated data, may be taken into account at the design stage. A design algorithm has been derived. For a linear Gaussian observation model the limit performance of any encoding-decoding scheme has been obtained in terms of an upper bound to the rate-distortion function. Under various combinations of per-channel signal-to-noise ratios and spatial correlation coefficients, quantizers designed by the proposed algorithm nearly achieve such limit performance.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/10120
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact