{"title":"矢量量化的自删除神经网络","authors":"M. Maeda, H. Miyajima, S. Murashima","doi":"10.1109/APCAS.1996.569208","DOIUrl":null,"url":null,"abstract":"Vector quantization is required the algorithm that minimizes the distortion error, and used for both storage and transmission of speech and image data. For a neural vector quantization, the self-creating neural network and self-deleting neural network and known for showing fine characters. In this paper, we improve the self-deleting neural network, and propose a generalization algorithm combining the creating and deleting neural networks. We discuss algorithms with neighborhood relations compared with the proposed one. Experimental results show the effectiveness of the proposed algorithm.","PeriodicalId":20507,"journal":{"name":"Proceedings of APCCAS'96 - Asia Pacific Conference on Circuits and Systems","volume":"76 1","pages":"18-21"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A self-deleting neural network for vector quantization\",\"authors\":\"M. Maeda, H. Miyajima, S. Murashima\",\"doi\":\"10.1109/APCAS.1996.569208\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vector quantization is required the algorithm that minimizes the distortion error, and used for both storage and transmission of speech and image data. For a neural vector quantization, the self-creating neural network and self-deleting neural network and known for showing fine characters. In this paper, we improve the self-deleting neural network, and propose a generalization algorithm combining the creating and deleting neural networks. We discuss algorithms with neighborhood relations compared with the proposed one. Experimental results show the effectiveness of the proposed algorithm.\",\"PeriodicalId\":20507,\"journal\":{\"name\":\"Proceedings of APCCAS'96 - Asia Pacific Conference on Circuits and Systems\",\"volume\":\"76 1\",\"pages\":\"18-21\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of APCCAS'96 - Asia Pacific Conference on Circuits and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCAS.1996.569208\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of APCCAS'96 - Asia Pacific Conference on Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCAS.1996.569208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A self-deleting neural network for vector quantization
Vector quantization is required the algorithm that minimizes the distortion error, and used for both storage and transmission of speech and image data. For a neural vector quantization, the self-creating neural network and self-deleting neural network and known for showing fine characters. In this paper, we improve the self-deleting neural network, and propose a generalization algorithm combining the creating and deleting neural networks. We discuss algorithms with neighborhood relations compared with the proposed one. Experimental results show the effectiveness of the proposed algorithm.