Synthesis of Correlated Multichannel Random Processes

J. H. Michels; P. K. Varshney; D. D. Weiner

doi:10.1109/78.275609

Synthesis of Correlated Multichannel Random Processes

J. H. Michels, P. K. Varshney, D. D. Weiner

Department of Electrical Engineering & Computer Science

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

This paper describes a method for synthesizine multichannel autoregressive (AR) random processes. The procedure allows for the variation of temporal and cross-channel correlation subject to specific constraints for correlation functions. The resulting synthesized processes provide a “fit” in a minimum mean squared error (MMSE) sense to the process correlation functions specified in terms of their temporal and cross-channel correlation parameters. Computer simulation results are presented showing the case of a two-channel AR process with various values of temporal and cross-channel correlation. A method is also suggested to synthesize a more general class of Gaussian processes with unconstrained quadrature components.

Original language	English (US)
Pages (from-to)	367-375
Number of pages	9
Journal	IEEE Transactions on Signal Processing
Volume	42
Issue number	2
DOIs	https://doi.org/10.1109/78.275609
State	Published - Feb 1994

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

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10.1109/78.275609

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title = "Synthesis of Correlated Multichannel Random Processes",

abstract = "This paper describes a method for synthesizine multichannel autoregressive (AR) random processes. The procedure allows for the variation of temporal and cross-channel correlation subject to specific constraints for correlation functions. The resulting synthesized processes provide a “fit” in a minimum mean squared error (MMSE) sense to the process correlation functions specified in terms of their temporal and cross-channel correlation parameters. Computer simulation results are presented showing the case of a two-channel AR process with various values of temporal and cross-channel correlation. A method is also suggested to synthesize a more general class of Gaussian processes with unconstrained quadrature components.",

author = "Michels, {J. H.} and Varshney, {P. K.} and Weiner, {D. D.}",

note = "Funding Information: Manuscript received April 7, 1992; revised January 13, 1993. The associate editor coordinating the review of this paper and approving it for publication was Prof. John Goutsias. This work was supported jointly by an in-house Rome Laboratory effort under project 4506 and AFOSR project 2305J8. .I.M ichels is with the Rome Laboratory, Griffiss A m , NY 13441-4514. P. Varshnev and D. Weiner are with the Deuartment of Electrical and Computer Engineering, Syracuse University, Syracuse, NY 13244-1240. IEEE Log Number 9214198.",

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AU - Weiner, D. D.

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N2 - This paper describes a method for synthesizine multichannel autoregressive (AR) random processes. The procedure allows for the variation of temporal and cross-channel correlation subject to specific constraints for correlation functions. The resulting synthesized processes provide a “fit” in a minimum mean squared error (MMSE) sense to the process correlation functions specified in terms of their temporal and cross-channel correlation parameters. Computer simulation results are presented showing the case of a two-channel AR process with various values of temporal and cross-channel correlation. A method is also suggested to synthesize a more general class of Gaussian processes with unconstrained quadrature components.

AB - This paper describes a method for synthesizine multichannel autoregressive (AR) random processes. The procedure allows for the variation of temporal and cross-channel correlation subject to specific constraints for correlation functions. The resulting synthesized processes provide a “fit” in a minimum mean squared error (MMSE) sense to the process correlation functions specified in terms of their temporal and cross-channel correlation parameters. Computer simulation results are presented showing the case of a two-channel AR process with various values of temporal and cross-channel correlation. A method is also suggested to synthesize a more general class of Gaussian processes with unconstrained quadrature components.

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Synthesis of Correlated Multichannel Random Processes

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