Novel Compression Techniques for Time Series Signals
Oinam Suchitra Devi1, Hemanth Kumar P.2, S Basavaraj Patil3
1Oinam Suchitra Devi.
2Hemanth Kumar P..
3S Basavaraj Patil.
Manuscript received on June 11, 2013. | Revised Manuscript received on June 15, 2013. | Manuscript published on June 25, 2013. | PP: 20-25 | Volume-1 Issue-8, June 2013. | Retrieval Number: H0343061813/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A time series signal can be defined as a sequence of data items which is measured through repeated measurements over uniform time intervals. Time series analysis comprises techniques for analyzing time series data in order to obtain meaningful statistics and other characteristics of the data transmission time. Compression is the techniques of reduction in size of data in order to save space or transmission time. Wavelet compression technique is a form of data compression well defined for image compression. The design of time series signal compression techniques involves trade-offs among various factors which includes the degree of compressing the data, the amount of distortion introduced and the computational resources required to compress and decompress the time series data. This paper analyzes different wavelet compression techniques like Wavelet Decomposition, Wavelet Packet, Decimated Discrete Wavelet, Fixed encoding, Huffman encoding and Novel Encoding Compression technique. Analyzing this paper discuss about novel approach for compressing time series signal. There exist several measures to know the quality of the reconstructed time series signal after compression of signal data. The most popularly used measured parameters are Percentage Root mean square Difference (PRD), Peak Signal to Noise Ratio (PSNR) and Maximal Absolute Difference (MAD) etc. From the results it is observed that Novel Compression Encoding technique gives better performance in compression of time series signal as it achieve high PSNR with better quality of compression, smaller PRD and MAD with less distortion compare to other compression techniques.
Keywords: Decimated Discrete Wavelet, Fixed encoding, Huffman encoding, Wavelet Decomposition, Wavelet Packet