Blind Separation of Non-Stationary Convolutively Mixed Signals in the Time Domain

Iain Russell; Jiangtao Xi; Alfred Mertins; Joe Chicharo

Blind Separation of Non-Stationary Convolutively Mixed Signals in the Time Domain

Iain Russell, Jiangtao Xi, Alfred Mertins, Joe Chicharo

Institute of Signal Processing

University of Wollongong

Abstract

This paper proposes a new algorithm for solving the Blind Signal Separation (BSS) problem for convolutive mixing completely in the time domain. The closed form expressions used for first and second order optimization techniques derived in [1] are extended to accommodate the more practical convolutive mixing scenario. Traditionally convolutive BSS problems are solved in the frequency domain [2], [3], [4] but this requires additional solving of the inherent frequency permutation problem. We demonstrate the performance of the algorithm using two optimization methods with a convolutive synthetic mixing system and real speech data.

Original language	English
Pages	93-98
Number of pages	6
Publication status	Published - 01.12.2003
Event	7th International Symposium on DSP for Communication Systems - Coolangatta, Australia Duration: 01.12.2003 → 03.12.2003

Conference

Conference	7th International Symposium on DSP for Communication Systems
Abbreviated title	DSPCS03
Country/Territory	Australia
City	Coolangatta
Period	01.12.03 → 03.12.03

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

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Cite this

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title = "Blind Separation of Non-Stationary Convolutively Mixed Signals in the Time Domain",

abstract = "This paper proposes a new algorithm for solving the Blind Signal Separation (BSS) problem for convolutive mixing completely in the time domain. The closed form expressions used for first and second order optimization techniques derived in [1] are extended to accommodate the more practical convolutive mixing scenario. Traditionally convolutive BSS problems are solved in the frequency domain [2], [3], [4] but this requires additional solving of the inherent frequency permutation problem. We demonstrate the performance of the algorithm using two optimization methods with a convolutive synthetic mixing system and real speech data. ",

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AU - Russell, Iain

AU - Xi, Jiangtao

AU - Mertins, Alfred

AU - Chicharo, Joe

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Y1 - 2003/12/1

N2 - This paper proposes a new algorithm for solving the Blind Signal Separation (BSS) problem for convolutive mixing completely in the time domain. The closed form expressions used for first and second order optimization techniques derived in [1] are extended to accommodate the more practical convolutive mixing scenario. Traditionally convolutive BSS problems are solved in the frequency domain [2], [3], [4] but this requires additional solving of the inherent frequency permutation problem. We demonstrate the performance of the algorithm using two optimization methods with a convolutive synthetic mixing system and real speech data.

AB - This paper proposes a new algorithm for solving the Blind Signal Separation (BSS) problem for convolutive mixing completely in the time domain. The closed form expressions used for first and second order optimization techniques derived in [1] are extended to accommodate the more practical convolutive mixing scenario. Traditionally convolutive BSS problems are solved in the frequency domain [2], [3], [4] but this requires additional solving of the inherent frequency permutation problem. We demonstrate the performance of the algorithm using two optimization methods with a convolutive synthetic mixing system and real speech data.

UR - https://www.researchgate.net/publication/228685813_BLIND_SEPARATION_OF_NON-STATIONARY_CONVOLUTIVELY_MIXED_SIGNALS_IN_THE_TIME_DOMAIN

M3 - Conference Papers

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T2 - 7th International Symposium on DSP for Communication Systems

Y2 - 1 December 2003 through 3 December 2003

ER -

Blind Separation of Non-Stationary Convolutively Mixed Signals in the Time Domain

Abstract

Conference

UN SDGs

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