Please use this identifier to cite or link to this item: https://doi.org/10.1109/78.205712
DC FieldValue
dc.titleThe Role of Integer Matrices in Multidimensional Multirate Systems
dc.contributor.authorChen T.
dc.contributor.authorVaidyanathan P.P.
dc.date.accessioned2018-08-21T05:14:10Z
dc.date.available2018-08-21T05:14:10Z
dc.date.issued1993
dc.identifier.citationChen T., Vaidyanathan P.P. (1993). The Role of Integer Matrices in Multidimensional Multirate Systems. IEEE Transactions on Signal Processing 41 (3) : 1035-1047. ScholarBank@NUS Repository. https://doi.org/10.1109/78.205712
dc.identifier.issn1053587X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/146450
dc.description.abstractThe basic building blocks in a multidimensional (MD) multirate system are the decimation matrix M and the expansion matrix L. For the D-dimensional case these are D � D nonsingular integer matrices. When these matrices are diagonal, most of the one-dimensional (ID) results can be extended automatically. However, for the nondiagonal case, these extensions are nontrivial. Some of these extensions, e.g., polyphase decomposition and maximally decimated perfect reconstruction systems have already been successfully made by some authors. However, there exist several ID results in multirate processing, for which the multidimensional extensions are even more difficult. An example is the development of polyphase representation for rational (rather than integer) sampling rate alterations. In the ID case, this development relies on the commutativity of decimators and expanders, which is possible whenever Mand L are relatively prime (coprime). The conditions for commutativity in the two-dimensional (2D) case have recently been developed successfully in [1], In the MD case, the results are more involved. In this paper we formulate and solve a number of problems of this nature. Our discussions are based on several key properties of integer matrices, including greatest common divisors and least common multiples, which we first review. These properties are analogous to those of polynomial matrices, some of which have been used in system theoretic work (e.g., matrix fraction descriptions, coprime matrices, Smith form, and so on).
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentOFFICE OF THE PROVOST
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.doi10.1109/78.205712
dc.description.sourcetitleIEEE Transactions on Signal Processing
dc.description.volume41
dc.description.issue3
dc.description.page1035-1047
dc.published.statepublished
dc.grant.idMIP 8919196
dc.grant.idMIP 8604456
dc.grant.fundingagencyNSF, National Science Foundation
dc.grant.fundingagencyIEEE, IEEE Foundation
dc.grant.fundingagencyDepartment of Electrical Engineering, Chulalongkorn University
dc.grant.fundingagencyCaltech, California Institute of Technology
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