Please use this identifier to cite or link to this item: https://doi.org/10.1109/78.382395
DC FieldValue
dc.titleRole of Anticausal Inverses in Multirate Filter-Banks-Part I: System-Theoretic Fundamentals
dc.contributor.authorVaidyanathan P.P.
dc.contributor.authorChen T.
dc.date.accessioned2018-08-21T05:13:45Z
dc.date.available2018-08-21T05:13:45Z
dc.date.issued1995
dc.identifier.citationVaidyanathan P.P., Chen T. (1995). Role of Anticausal Inverses in Multirate Filter-Banks-Part I: System-Theoretic Fundamentals. IEEE Transactions on Signal Processing 43 (5) : 1090-1102. ScholarBank@NUS Repository. https://doi.org/10.1109/78.382395
dc.identifier.issn1053587X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/146433
dc.description.abstractIn a maximally decimated filter bank with identical decimation ratios for all channels, the perfect reconstructibility property and the nature of reconstruction filters (causality, stability, FIR property, and so on) depend on the properties of the polyphase matrix. Various properties and capabilities of the filter bank depend on the properties of the polyphase matrix as well as the nature of its inverse. In this paper we undertake a study of the types of inverses and characterize them according to their system theoretic properties (i.e., properties of state-space descriptions, McMillan degree, degree of determinant, and so forth). We find in particular that causal polyphase matrices with anticausal inverses have an important role in filter bank theory. We study their properties both for the FIR and HR cases. Techniques for implementing anticausal IIR inverses based on state space descriptions are outlined. It is found that causal FIR matrices with anticausal FIR inverses (cafacafi) have a key role in the characterization of FIR filter banks. In a companion paper, these results are applied for the factorization of biorthogonal FIR filter banks, and a generalization of the lapped orthogonal transform called the biorthogonal lapped transform (BOLT) developed.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentOFFICE OF THE PROVOST
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.doi10.1109/78.382395
dc.description.sourcetitleIEEE Transactions on Signal Processing
dc.description.volume43
dc.description.issue5
dc.description.page1090-1102
dc.published.statepublished
dc.grant.idN00014-93-1-0231
dc.grant.fundingagencyIEEE, IEEE Foundation
dc.grant.fundingagencyONR, Office of Naval Research
dc.grant.fundingagencyCaltech, California Institute of Technology
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