Please use this identifier to cite or link to this item:
https://doi.org/10.1109/78.205712
DC Field | Value | |
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dc.title | The Role of Integer Matrices in Multidimensional Multirate Systems | |
dc.contributor.author | Chen T. | |
dc.contributor.author | Vaidyanathan P.P. | |
dc.date.accessioned | 2018-08-21T05:14:10Z | |
dc.date.available | 2018-08-21T05:14:10Z | |
dc.date.issued | 1993 | |
dc.identifier.citation | Chen 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.issn | 1053587X | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/146450 | |
dc.description.abstract | The 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.source | Scopus | |
dc.type | Article | |
dc.contributor.department | OFFICE OF THE PROVOST | |
dc.contributor.department | DEPARTMENT OF COMPUTER SCIENCE | |
dc.description.doi | 10.1109/78.205712 | |
dc.description.sourcetitle | IEEE Transactions on Signal Processing | |
dc.description.volume | 41 | |
dc.description.issue | 3 | |
dc.description.page | 1035-1047 | |
dc.published.state | published | |
dc.grant.id | MIP 8919196 | |
dc.grant.id | MIP 8604456 | |
dc.grant.fundingagency | NSF, National Science Foundation | |
dc.grant.fundingagency | IEEE, IEEE Foundation | |
dc.grant.fundingagency | Department of Electrical Engineering, Chulalongkorn University | |
dc.grant.fundingagency | Caltech, California Institute of Technology | |
Appears in Collections: | Staff Publications |
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