Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting

Compound smoother is a non-linear smoothing technique that has the ability to reduce heavy noise from signal and at the same time, is resistant to sudden changes and impulse in a data series. The compound smoother of 4253HT has been studied and modified in the algorithm, specifically to estimate the...

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Main Author:	Khairol Azmi, Nurul Nisa'
Format:	Thesis
Language:	English
Published:	2019
Subjects:	Mathematical models Signal processing
Online Access:	http://psasir.upm.edu.my/id/eprint/79207/1/IPM%202019%2014%20ir.pdf
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spelling	my-upm-ir.792072022-01-12T04:11:55Z Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting 2019-02 Khairol Azmi, Nurul Nisa' Compound smoother is a non-linear smoothing technique that has the ability to reduce heavy noise from signal and at the same time, is resistant to sudden changes and impulse in a data series. The compound smoother of 4253HT has been studied and modified in the algorithm, specifically to estimate the middle point of running median for even span size by applying the following types of means; geometric, harmonic, quadratic and contraharmonic. The stability of running median of even span with modification toward the positive and negative block pulse were discussed. The modified 4253HT using harmonic mean works best in preserving edge at sudden changes point from down to upward and negative block pulse. Modified 4253HT using contraharmonic mean on the other hand, has been found to preserve edge of upward point and positive block pulse. The combination of modified 4253HT using harmonic and contraharmonic means adaptively, produce a new smoother with more resistance to block pulse and better preservation of the edge. The performance of the modified compound smoothers was assessed via simulation. The signal of sinusoidal and special functions; Doppler, HeavySine, Bumps and Block was generated with non-Gaussian noise added that produced high volatility and disturbed by outliers. The performance were measured by regression coefficient, Estimated Integrated Mean Square Error (EIMSE) and variance reduction. The 4253HT has the ability to capture the signal from heavy noise data. In general, 4253HT performs best at smaller frequency and the recovery of signal from heavy noise at high frequency using 4253HT is fairly good. This is asserted by the smooth value which was close to the signal, indicating its capability to extract signal from highly fluctuating noise. The modified 4253HT using adaptive mean showed the most effective, compared to others, in extracting low, moderate and high frequency of sinusoidal signal from the noise with 10%, 25%, 50% and 75% contaminated normal distribution. The Doppler, Block, Bumps and Heavy Sine signal show the modified 4253HT using adaptive mean also managed to recover those signal from noise better than other modified 4253HT and the existing one. The extracted signal was then used for better forecasting which was facilitated by seasonal Holt-Winters, ARAR and seasonal ARIMA algorithm. Mathematical models Signal processing 2019-02 Thesis http://psasir.upm.edu.my/id/eprint/79207/ http://psasir.upm.edu.my/id/eprint/79207/1/IPM%202019%2014%20ir.pdf text en public doctoral Universiti Putra Malaysia Mathematical models Signal processing Adam, Mohd Bakri
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Adam, Mohd Bakri
topic	Mathematical models Signal processing
spellingShingle	Mathematical models Signal processing Khairol Azmi, Nurul Nisa' Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
description	Compound smoother is a non-linear smoothing technique that has the ability to reduce heavy noise from signal and at the same time, is resistant to sudden changes and impulse in a data series. The compound smoother of 4253HT has been studied and modified in the algorithm, specifically to estimate the middle point of running median for even span size by applying the following types of means; geometric, harmonic, quadratic and contraharmonic. The stability of running median of even span with modification toward the positive and negative block pulse were discussed. The modified 4253HT using harmonic mean works best in preserving edge at sudden changes point from down to upward and negative block pulse. Modified 4253HT using contraharmonic mean on the other hand, has been found to preserve edge of upward point and positive block pulse. The combination of modified 4253HT using harmonic and contraharmonic means adaptively, produce a new smoother with more resistance to block pulse and better preservation of the edge. The performance of the modified compound smoothers was assessed via simulation. The signal of sinusoidal and special functions; Doppler, HeavySine, Bumps and Block was generated with non-Gaussian noise added that produced high volatility and disturbed by outliers. The performance were measured by regression coefficient, Estimated Integrated Mean Square Error (EIMSE) and variance reduction. The 4253HT has the ability to capture the signal from heavy noise data. In general, 4253HT performs best at smaller frequency and the recovery of signal from heavy noise at high frequency using 4253HT is fairly good. This is asserted by the smooth value which was close to the signal, indicating its capability to extract signal from highly fluctuating noise. The modified 4253HT using adaptive mean showed the most effective, compared to others, in extracting low, moderate and high frequency of sinusoidal signal from the noise with 10%, 25%, 50% and 75% contaminated normal distribution. The Doppler, Block, Bumps and Heavy Sine signal show the modified 4253HT using adaptive mean also managed to recover those signal from noise better than other modified 4253HT and the existing one. The extracted signal was then used for better forecasting which was facilitated by seasonal Holt-Winters, ARAR and seasonal ARIMA algorithm.
format	Thesis
qualification_level	Doctorate
author	Khairol Azmi, Nurul Nisa'
author_facet	Khairol Azmi, Nurul Nisa'
author_sort	Khairol Azmi, Nurul Nisa'
title	Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
title_short	Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
title_full	Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
title_fullStr	Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
title_full_unstemmed	Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
title_sort	efficiency of 4253ht smoothers in extracting signal from noise and their applications in forecasting
granting_institution	Universiti Putra Malaysia
publishDate	2019
url	http://psasir.upm.edu.my/id/eprint/79207/1/IPM%202019%2014%20ir.pdf
_version_	1747813310567284736

Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting

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