{"title":"基于改进粒子群优化的矢量量化码本设计","authors":"Jifeng Sun, Jinhua Ouyang","doi":"10.1109/ICACTE.2010.5579330","DOIUrl":null,"url":null,"abstract":"An improved particle swarm optimization scheme for codebook design is proposed in this paper. By sorting the training vector, we select the initial codebook to enhance the diversity of search, and add stagnant judging algebra to prevent the algorithm falling into a local optimum. The simulation results prove that the improved method is reasonable.","PeriodicalId":255806,"journal":{"name":"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Codebook design of vector quantization based on improved particle swarm optimization\",\"authors\":\"Jifeng Sun, Jinhua Ouyang\",\"doi\":\"10.1109/ICACTE.2010.5579330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved particle swarm optimization scheme for codebook design is proposed in this paper. By sorting the training vector, we select the initial codebook to enhance the diversity of search, and add stagnant judging algebra to prevent the algorithm falling into a local optimum. The simulation results prove that the improved method is reasonable.\",\"PeriodicalId\":255806,\"journal\":{\"name\":\"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)\",\"volume\":\"106 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACTE.2010.5579330\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACTE.2010.5579330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Codebook design of vector quantization based on improved particle swarm optimization
An improved particle swarm optimization scheme for codebook design is proposed in this paper. By sorting the training vector, we select the initial codebook to enhance the diversity of search, and add stagnant judging algebra to prevent the algorithm falling into a local optimum. The simulation results prove that the improved method is reasonable.