Publication Type:

Conference Paper

Source:

IEEE Region 10 Annual International Conference, Proceedings/TENCON, Institute of Electrical and Electronics Engineers Inc., p.3809-3812 (2017)

ISBN:

9781509025961

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015440724&doi=10.1109%2fTENCON.2016.7848776&partnerID=40&md5=1abe4ae84d2df3c236255ff2512a012d

Keywords:

Decomposition level, Decomposition trees, Forestry, Multicomponent signals, Principal Components, Processing time, Signal processing, Spectral representations, Subband decomposition, Synthetic signals

Abstract:

This paper presents a spectral subband decomposition using G-lets in time-domain for 1-D and 2-D signals. The decomposition is achieved through successive filtering and decimation steps ending up in a decomposition tree. At each node of the tree, the parameters of the corresponding subband signal are estimated using high gradients obtained at the first node. The resulting subbands are found to highlight the components of the signal. The proposed method using G-lets enables one to reduce the processing time and makes the choice of decomposition levels easier, comparatively to the case where the whole signal is processed at once. The advantage of G-lets based subbands is demonstrated using 1-D and 2-D signals. It is seen that a synthetic signal generated from a sine and cosine signal is separated into exactly the same two signals and the performance is good for monocomponent and multicomponent signals. © 2016 IEEE.

Notes:

cited By 0; Conference of 2016 IEEE Region 10 Conference, TENCON 2016 ; Conference Date: 22 November 2016 Through 25 November 2016; Conference Code:126432

Cite this Research Publication

Dr. Rajathilagam B. and Rangarajan, M., “Spectral representation of principal components in signals and images using G-lets decomposition of subbands”, in IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017, pp. 3809-3812.

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