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Predictive Algorithm Based Low Complexity 2D FastICA

Predictive Algorithm Based Low Complexity 2D FastICA
Predictive Algorithm Based Low Complexity 2D FastICA
Abstract—FastICA (FICA) is a popular algorithm in solving Blind Source Separation (BSS) problem. It mainly involves solving an adaptive iterative equation for computing the constituent vectors of the unmixing matrix to be estimated. Each of these iterations includes adaptive equation computation, normalization and orthogonalization which need significant amount of complex arithmetic operations such as multiplications, divisions and square rooting. For commonly used 2-dimensional FICA, the unmixing matrix consists of two vectors each of which is computed by running such FICA Iteration several times until convergence is achieved. In this paper we propose an algorithm that predicts the second vector of the unmixing matrix from the first one without any numerical calculation and thereby reduces the overall arithmetic computation complexity significantly by removing one complete stage of FICA Iteration. Subsequently analysis is carried out in terms of computational complexity and delay with respect to varying framelength, wordlength and number of iteration of convergence and compared with the previously reported 2D FICA architectures.
Blind Source Separation, Independent Component Analysis, FastICA, Low Power VLSI Architecture.
Acharyya, Amit
f7c95a87-04ac-4d13-a74c-0c4d89b1c79c
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Acharyya, Amit
f7c95a87-04ac-4d13-a74c-0c4d89b1c79c
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d

Acharyya, Amit, Maharatna, Koushik and Al-Hashimi, Bashir (2011) Predictive Algorithm Based Low Complexity 2D FastICA. UK Electronics Forum 2011, United Kingdom. 04 - 05 Jul 2011. (Submitted)

Record type: Conference or Workshop Item (Other)

Abstract

Abstract—FastICA (FICA) is a popular algorithm in solving Blind Source Separation (BSS) problem. It mainly involves solving an adaptive iterative equation for computing the constituent vectors of the unmixing matrix to be estimated. Each of these iterations includes adaptive equation computation, normalization and orthogonalization which need significant amount of complex arithmetic operations such as multiplications, divisions and square rooting. For commonly used 2-dimensional FICA, the unmixing matrix consists of two vectors each of which is computed by running such FICA Iteration several times until convergence is achieved. In this paper we propose an algorithm that predicts the second vector of the unmixing matrix from the first one without any numerical calculation and thereby reduces the overall arithmetic computation complexity significantly by removing one complete stage of FICA Iteration. Subsequently analysis is carried out in terms of computational complexity and delay with respect to varying framelength, wordlength and number of iteration of convergence and compared with the previously reported 2D FICA architectures.

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Submitted date: 4 July 2011
Additional Information: Event Dates: 4-5 July, 2011
Venue - Dates: UK Electronics Forum 2011, United Kingdom, 2011-07-04 - 2011-07-05
Keywords: Blind Source Separation, Independent Component Analysis, FastICA, Low Power VLSI Architecture.
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 272268
URI: https://eprints.soton.ac.uk/id/eprint/272268
PURE UUID: 466ec84c-c3d7-4242-896d-d306bbbeb3ea

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Date deposited: 10 May 2011 14:14
Last modified: 01 Dec 2017 17:33

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Contributors

Author: Amit Acharyya

University divisions

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