基于小波包的时变二次模型选择

信号处理 Pub Date : 2001-08-06 DOI:10.1109/SSP.2001.955293

M. Green

{"title":"基于小波包的时变二次模型选择","authors":"M. Green","doi":"10.1109/SSP.2001.955293","DOIUrl":null,"url":null,"abstract":"Model selection and system identification for cases where the model is required to have both characteristics of time-variance and nonlinearity is considered. To enable identification from a single input/output observation record, the time-variation is approximated by a weighted sum of orthogonal sequences. Wavelet packets are chosen for these sequences and an adapted basis for each time-varying coefficient is selected via the best basis algorithm. Individual wavelet packets are then selected via a multiple hypothesis test which determines those packets that are significant to each approximation, and which may be discarded from the model.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"5 1","pages":"345-348"},"PeriodicalIF":0.0000,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time-varying quadratic model selection using wavelet packets\",\"authors\":\"M. Green\",\"doi\":\"10.1109/SSP.2001.955293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Model selection and system identification for cases where the model is required to have both characteristics of time-variance and nonlinearity is considered. To enable identification from a single input/output observation record, the time-variation is approximated by a weighted sum of orthogonal sequences. Wavelet packets are chosen for these sequences and an adapted basis for each time-varying coefficient is selected via the best basis algorithm. Individual wavelet packets are then selected via a multiple hypothesis test which determines those packets that are significant to each approximation, and which may be discarded from the model.\",\"PeriodicalId\":70952,\"journal\":{\"name\":\"信号处理\",\"volume\":\"5 1\",\"pages\":\"345-348\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"信号处理\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1109/SSP.2001.955293\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"信号处理","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/SSP.2001.955293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

考虑了模型同时具有时变和非线性特性的情况下的模型选择和系统辨识。为了能够从单个输入/输出观测记录中进行识别，时间变化通过正交序列的加权和来近似。对这些序列选择小波包，并通过最佳基算法为每个时变系数选择一个自适应基。然后通过多重假设检验选择单个小波包，该检验确定那些对每个近似都重要的包，并且可以从模型中丢弃。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Time-varying quadratic model selection using wavelet packets

Model selection and system identification for cases where the model is required to have both characteristics of time-variance and nonlinearity is considered. To enable identification from a single input/output observation record, the time-variation is approximated by a weighted sum of orthogonal sequences. Wavelet packets are chosen for these sequences and an adapted basis for each time-varying coefficient is selected via the best basis algorithm. Individual wavelet packets are then selected via a multiple hypothesis test which determines those packets that are significant to each approximation, and which may be discarded from the model.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

信号处理

自引率

0.00%

发文量

5812

期刊介绍： Journal of Signal Processing is an academic journal supervised by China Association for Science and Technology and sponsored by China Institute of Electronics. The journal is an academic journal that reflects the latest research results and technological progress in the field of signal processing and related disciplines. It covers academic papers and review articles on new theories, new ideas, and new technologies in the field of signal processing. The journal aims to provide a platform for academic exchanges for scientific researchers and engineering and technical personnel engaged in basic research and applied research in signal processing, thereby promoting the development of information science and technology. At present, the journal has been included in the three major domestic core journal databases "China Science Citation Database (CSCD), China Science and Technology Core Journals (CSTPCD), Chinese Core Journals Overview" and Coaj. It is also included in many foreign databases such as Scopus, CSA, EBSCO host, INSPEC, JST, etc.