{"title":"The optimum reconstruction of vector signals using multi-input multi-output filter banks","authors":"Y. Kida, T. Kida","doi":"10.1109/ICDSP.2011.6004939","DOIUrl":null,"url":null,"abstract":"In this paper, we define a multi-input multi-output system composed of given analysis-filter matrices, given sampler matrices and interpolation-filter matrices to be optimized, respectively. It is assumed that input-signal vectors of this system are contained in a certain given set of input-signal vectors. Firstly, we define new notations which expresses a kind of product between two matrices or between a vector and a matrix. Using these new notations, we show that the presented approximation satisfies a certain two conditions and prove that the presented approximation minimizes any upperlimit measure of error compared to any other linear or nonlinear approximation with same sample values, simultaneously.","PeriodicalId":360702,"journal":{"name":"2011 17th International Conference on Digital Signal Processing (DSP)","volume":"42 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 17th International Conference on Digital Signal Processing (DSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2011.6004939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, we define a multi-input multi-output system composed of given analysis-filter matrices, given sampler matrices and interpolation-filter matrices to be optimized, respectively. It is assumed that input-signal vectors of this system are contained in a certain given set of input-signal vectors. Firstly, we define new notations which expresses a kind of product between two matrices or between a vector and a matrix. Using these new notations, we show that the presented approximation satisfies a certain two conditions and prove that the presented approximation minimizes any upperlimit measure of error compared to any other linear or nonlinear approximation with same sample values, simultaneously.