Self-Similar Decomposition of Digital Signals

Author:

Alexiev Kiril M.1,Toshkov Teodor G.1,Prodanov Dimiter P.12

Affiliation:

1. Institute of Information and Communication Systems , Bulgarian Academy of Sciences , 1113 Sofia , Bulgaria

2. EHS and NERF, IMEC , Leuven , Belgium

Abstract

Abstract Traditionally, the engineers analyze signals in the time domain and in the frequency domain. These signal representations discover different signal characteristics and in many cases, the exploration of a single signal presentation is not sufficient. In the present paper, a new self-similar decomposition of digital signals is proposed. Unlike some well-known approaches, the newly proposed method for signal decomposition and description does not use pre-selected templates such as sine waves, wavelets, etc. It is realized in time domain but at the same time, it contains information about frequency signal characteristics. Good multiscale characteristics of the algorithm being proposed are demonstrated in a series of examples. It can be used for compact signal presentation, restoration of distorted signals, event detection, localization, etc. The method is also suitable for description of highly repetitive continuous and digital signals.

Publisher

Walter de Gruyter GmbH

Subject

General Computer Science

Reference20 articles.

1. 1. Fourier, J. The Analytical Theory of Heat. New York, Cosimo, Inc., 2007, ISBN: 978-1-60206-107-1, Originally Published in 1822.

2. 2. Cooley, J. W., J. W. Tukey. An Algorithm for the Machine Calculation of Complex Fourier Series. – Mathematics of Computation, Vol. 19, No 90, pp. 297-301. DOI:10.1090/S0025-5718-1965-0178586-1, ISSN 0025-5718.10.1090/S0025-5718-1965-0178586-1

3. 3. Krivosheew, V. I. Contemporary Methods for Digital Signal Processing (Digital Spectral Analysis). Educational-Methodical Material for the Advanced Training Program “Modern Mobile Digital Communication Systems, Problems of Noise Immunity and Information Protection”. Nijnii Novgorod, 2006 (in Russian).

4. 4. Besl, P. J., R. C. Jain. Segmentation through Variable-Order Surface Fitting. – IEEE Trans. on PAMI, Vol. IO, March 1988, No 2, pp. 167-192.10.1109/34.3881

5. 5. Allen, R. L., D. W. Mills. Signal Analysis Time, Frequency, Scale, and Structure. Copyright © 2004 by the Institute of Electrical and Electronics Engineers, Inc., ISBN: 0-471-23441-9.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3