Nonstationary signal reconstruction from TVAR coefficients

Nonstationary signal (NSS) reconstruction from Time Varying (TV) coefficients of Time Varying Autoregressive (TVAR) process is presented in this paper. The proposed method consists of three steps, where in the first step, initial values for TVAR coefficients are estimated from synaptic weights of a...

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Main Authors:	Najeeb, Athaur Rahman, Gunawan, Teddy Surya, Aibinu, Abiodun Musa
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2018
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/60066/ http://irep.iium.edu.my/60066/ http://irep.iium.edu.my/60066/ http://irep.iium.edu.my/60066/1/60066_Nonstationary%20signal%20reconstruction%20from%20TVAR_complete.pdf http://irep.iium.edu.my/60066/2/60066_Nonstationary%20signal%20reconstruction%20from%20TVAR_scopus.pdf

id	iium-60066
recordtype	eprints
spelling	iium-600662018-11-08T05:26:37Z http://irep.iium.edu.my/60066/ Nonstationary signal reconstruction from TVAR coefficients Najeeb, Athaur Rahman Gunawan, Teddy Surya Aibinu, Abiodun Musa TK Electrical engineering. Electronics Nuclear engineering Nonstationary signal (NSS) reconstruction from Time Varying (TV) coefficients of Time Varying Autoregressive (TVAR) process is presented in this paper. The proposed method consists of three steps, where in the first step, initial values for TVAR coefficients are estimated from synaptic weights of a three layer Artificial Neural Network (ANN) which is trained using Backpropagation (BP) learning algorithm. The estimated TVAR coefficients are then optimized using a Genetic Algorithm optimization algorithm for more accurate values in the second step. And finally once the TVAR coefficients are estimated using ANN and GA, it is then used to recover the original signal. Performance of proposed method has been evaluated by comparing reconstruction of various computer generated NSS from proposed methods with other methods. Five performance metrics was used for comparison where proposed method is shown to overcome the performance of other methods. Institute of Electrical and Electronics Engineers Inc. 2018-03-09 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/60066/1/60066_Nonstationary%20signal%20reconstruction%20from%20TVAR_complete.pdf application/pdf en http://irep.iium.edu.my/60066/2/60066_Nonstationary%20signal%20reconstruction%20from%20TVAR_scopus.pdf Najeeb, Athaur Rahman and Gunawan, Teddy Surya and Aibinu, Abiodun Musa (2018) Nonstationary signal reconstruction from TVAR coefficients. In: 4th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2017, 28 - 30 November 2017, The Everly Putrajaya Hotel, Kuala Lumpur. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8311982 10.1109/ICSIMA.2017.8311982
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Najeeb, Athaur Rahman Gunawan, Teddy Surya Aibinu, Abiodun Musa Nonstationary signal reconstruction from TVAR coefficients
description	Nonstationary signal (NSS) reconstruction from Time Varying (TV) coefficients of Time Varying Autoregressive (TVAR) process is presented in this paper. The proposed method consists of three steps, where in the first step, initial values for TVAR coefficients are estimated from synaptic weights of a three layer Artificial Neural Network (ANN) which is trained using Backpropagation (BP) learning algorithm. The estimated TVAR coefficients are then optimized using a Genetic Algorithm optimization algorithm for more accurate values in the second step. And finally once the TVAR coefficients are estimated using ANN and GA, it is then used to recover the original signal. Performance of proposed method has been evaluated by comparing reconstruction of various computer generated NSS from proposed methods with other methods. Five performance metrics was used for comparison where proposed method is shown to overcome the performance of other methods.
format	Conference or Workshop Item
author	Najeeb, Athaur Rahman Gunawan, Teddy Surya Aibinu, Abiodun Musa
author_facet	Najeeb, Athaur Rahman Gunawan, Teddy Surya Aibinu, Abiodun Musa
author_sort	Najeeb, Athaur Rahman
title	Nonstationary signal reconstruction from TVAR coefficients
title_short	Nonstationary signal reconstruction from TVAR coefficients
title_full	Nonstationary signal reconstruction from TVAR coefficients
title_fullStr	Nonstationary signal reconstruction from TVAR coefficients
title_full_unstemmed	Nonstationary signal reconstruction from TVAR coefficients
title_sort	nonstationary signal reconstruction from tvar coefficients
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2018
url	http://irep.iium.edu.my/60066/ http://irep.iium.edu.my/60066/ http://irep.iium.edu.my/60066/ http://irep.iium.edu.my/60066/1/60066_Nonstationary%20signal%20reconstruction%20from%20TVAR_complete.pdf http://irep.iium.edu.my/60066/2/60066_Nonstationary%20signal%20reconstruction%20from%20TVAR_scopus.pdf
first_indexed	2023-09-18T21:25:08Z
last_indexed	2023-09-18T21:25:08Z
_version_	1777412141393903616

Nonstationary signal reconstruction from TVAR coefficients

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