A two stage vector quantization approach via self-organizing map Xu, Lixin, Liu, W. Q. and Venkatesh, Svetha 2002, A two stage vector quantization approach via self-organizing map, in ICSP' 02 : 6th International Conference on Signal Processing proceedings, IEEE, Piscataway, N. J., pp. 913-916, doi: 10.1109/ICOSP.2002.1181205. Attached Files Name Description MIMEType Size Downloads venkatesh-atwostage-2002.pdf Published version application/pdf 380.44KB 26 Title A two stage vector quantization approach via self-organizing map Author(s) Xu, Lixin Liu, W. Q. Venkatesh, Svetha Conference name International Conference on Signal Processing (6th : 2002 : Beijing, China) Conference location Beijing, China Conference dates 26-30 Aug. 2002 Title of proceedings ICSP' 02 : 6th International Conference on Signal Processing proceedings Editor(s) Baozong, Yuan Xiaofang, Tang Publication date 2002 Conference series International Conference on Signal Processing Start page 913 End page 916 Total pages 4 Publisher IEEE Place of publication Piscataway, N. J. Keyword(s) code standards computer networks convergence data compression distortion measurement euclidean distance neural networks nonlinear distortion organizing vector quantization Summary In this paper, a two-stage algorithm for vector quantization is proposed based on a self-organizing map (SOM) neural network. First, a conventional self-organizing map is modified to deal with dead codebooks in the learning process and is then used to obtain the codebook distribution structure for a given set of input data. Next, subblocks are classified based on the previous structure distribution with a prior criteria. Then, the conventional LBG algorithm is applied to these sub-blocks for data classification with initial values obtained via the SOM. Finally, extensive simulations illustrate that the proposed two-stage algorithm is very effective. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. ISBN 0780374886 Language eng DOI 10.1109/ICOSP.2002.1181205 Field of Research 089999 Information and Computing Sciences not elsewhere classified Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2002, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30044861 Document type: Conference Paper Collections: School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 01 May 2012, 11:03:01 EST Mon, 07 May 2012, 15:03:04 EST Mon, 07 May 2012, 15:10:56 EST Mon, 15 Sep 2014, 16:10:50 EST Tue, 06 Sep 2016, 18:52:32 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 251 Abstract Views, 26 File Downloads  -  Detailed Statistics Created: Tue, 01 May 2012, 11:03:01 EST

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