A novel signal diagnosis technique using pseudo complex-valued autoregressive technique
In this paper, a new method of biomedical signal classification using complex- valued pseudo autoregressive (CAR) modeling approach has been proposed. The CAR coefficients were computed from the synaptic weights and coefficients of a split weight and activation function of a feedforward multilayer...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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Elsevier
2011
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Online Access: | http://irep.iium.edu.my/1476/1/ESWA.pdf |
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author | Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin |
author_facet | Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin |
author_sort | Aibinu, Abiodun Musa |
collection | IIUM |
description | In this paper, a new method of biomedical signal classification using complex- valued pseudo autoregressive
(CAR) modeling approach has been proposed. The CAR coefficients were computed from the synaptic weights and coefficients of a split weight and activation function of a feedforward multilayer complex valued neural network. The performance of the proposed technique has been evaluated using PIMA Indian diabetes dataset with different complex-valued data normalization techniques and four different
values of learning rate. An accuracy value of 81.28% has been obtained using this proposed technique. |
first_indexed | 2024-03-05T22:29:25Z |
format | Article |
id | oai:generic.eprints.org:1476 |
institution | International Islamic University Malaysia |
language | English |
last_indexed | 2024-03-05T22:29:25Z |
publishDate | 2011 |
publisher | Elsevier |
record_format | dspace |
spelling | oai:generic.eprints.org:14762011-10-03T06:59:55Z http://irep.iium.edu.my/1476/ A novel signal diagnosis technique using pseudo complex-valued autoregressive technique Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin TA165 Engineering instruments, meters, etc. Industrial instrumentation In this paper, a new method of biomedical signal classification using complex- valued pseudo autoregressive (CAR) modeling approach has been proposed. The CAR coefficients were computed from the synaptic weights and coefficients of a split weight and activation function of a feedforward multilayer complex valued neural network. The performance of the proposed technique has been evaluated using PIMA Indian diabetes dataset with different complex-valued data normalization techniques and four different values of learning rate. An accuracy value of 81.28% has been obtained using this proposed technique. Elsevier 2011 Article PeerReviewed application/pdf en http://irep.iium.edu.my/1476/1/ESWA.pdf Aibinu, Abiodun Musa and Salami, Momoh Jimoh Emiyoka and Shafie, Amir Akramin (2011) A novel signal diagnosis technique using pseudo complex-valued autoregressive technique. Expert Systems with Application, 38 (8). pp. 9063-9069. ISSN 0957-4174 http://www.elsevier.com/wps/find/journaldescription.cws_home/939/description#description 10.1016/j.eswa.2010.11.005 |
spellingShingle | TA165 Engineering instruments, meters, etc. Industrial instrumentation Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin A novel signal diagnosis technique using pseudo complex-valued autoregressive technique |
title | A novel signal diagnosis technique using pseudo complex-valued autoregressive technique |
title_full | A novel signal diagnosis technique using pseudo complex-valued autoregressive technique |
title_fullStr | A novel signal diagnosis technique using pseudo complex-valued autoregressive technique |
title_full_unstemmed | A novel signal diagnosis technique using pseudo complex-valued autoregressive technique |
title_short | A novel signal diagnosis technique using pseudo complex-valued autoregressive technique |
title_sort | novel signal diagnosis technique using pseudo complex valued autoregressive technique |
topic | TA165 Engineering instruments, meters, etc. Industrial instrumentation |
url | http://irep.iium.edu.my/1476/1/ESWA.pdf |
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