{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T04:12:27Z","timestamp":1778299947071,"version":"3.51.4"},"reference-count":1,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[1999,6]]},"abstract":"<jats:p> Vector quantization plays an important role in many signal processing problems, such as speech\/speaker recognition and signal compression. This paper presents an unsupervised algorithm for vector quantizer design. Although the proposed method is inspired in Kohonen learning, it does not incorporate the classical definition of topological neighborhood as an array of nodes. Simulations are carried out to compare the performance of the proposed algorithm, named SOA (self-organizing algorithm), to that of the traditional LBG (Linde-Buzo-Gray) algorithm. The authors present an evaluation concerning the codebook design for Gauss-Markov and Gaussian sources, since the theoretic optimal performance bounds for these sources, as described by Shannon's Rate-Distortion Theory, are known. In speech and image compression, SOA codebooks lead to reconstructed (vector-quantized) signals with better quality as compared to the ones obtained by using LBG codebooks. Additionally, the influence of the initial codebook in the algorithm performance is investigated and the algorithm ability to learn representative patterns is evaluated. In a speaker identification system, it is shown that the the codebooks designed by SOA lead to higher identification rates when compared to the ones designed by LBG. <\/jats:p>","DOI":"10.1142\/s0129065799000216","type":"journal-article","created":{"date-parts":[[2003,5,14]],"date-time":"2003-05-14T07:53:01Z","timestamp":1052898781000},"page":"219-226","source":"Crossref","is-referenced-by-count":9,"title":["A Self-Organizing Algorithm for Vector Quantizer Design Applied to Signal Processing"],"prefix":"10.1142","volume":"09","author":[{"given":"F.","family":"MADEIRO","sequence":"first","affiliation":[{"name":"Laborat\u00f3rio De Automa\u00e7\u00e3o e Processamento De Sinais \u2013 LAPS, UFPB \u2013 CCT \u2013 Campus II \u2013 Departamento De Engenharia El\u00e9trica, 58.109-970 \u2013 Campina Grande, PB, Brasil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R. M.","family":"VILAR","sequence":"additional","affiliation":[{"name":"Laborat\u00f3rio De Automa\u00e7\u00e3o e Processamento De Sinais \u2013 LAPS, UFPB \u2013 CCT \u2013 Campus II \u2013 Departamento De Engenharia El\u00e9trica, 58.109-970 \u2013 Campina Grande, PB, Brasil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J. M.","family":"FECHINE","sequence":"additional","affiliation":[{"name":"Laborat\u00f3rio De Automa\u00e7\u00e3o e Processamento De Sinais \u2013 LAPS, UFPB \u2013 CCT \u2013 Campus II \u2013 Departamento De Engenharia El\u00e9trica, 58.109-970 \u2013 Campina Grande, PB, Brasil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B. G. AGUIAR","family":"NETO","sequence":"additional","affiliation":[{"name":"Laborat\u00f3rio De Automa\u00e7\u00e3o e Processamento De Sinais \u2013 LAPS, UFPB \u2013 CCT \u2013 Campus II \u2013 Departamento De Engenharia El\u00e9trica, 58.109-970 \u2013 Campina Grande, PB, Brasil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"p_15","author":"Design Vector Quantizer","journal-title":"IEEE Transactions on"}],"container-title":["International Journal of Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129065799000216","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T22:08:43Z","timestamp":1565129323000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129065799000216"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1999,6]]},"references-count":1,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1999,6]]}},"alternative-id":["10.1142\/S0129065799000216"],"URL":"https:\/\/doi.org\/10.1142\/s0129065799000216","relation":{},"ISSN":["0129-0657","1793-6462"],"issn-type":[{"value":"0129-0657","type":"print"},{"value":"1793-6462","type":"electronic"}],"subject":[],"published":{"date-parts":[[1999,6]]}}}