Time-varying computational networks: realization, lossless embedding, and structural factorization

Alle-Jan van der Veen; Patrick W. Dewilde

doi:10.1117/12.130927

30 November 1992 Time-varying computational networks: realization, lossless embedding, and structural factorization

Alle-Jan van der Veen, Patrick W. Dewilde

Proceedings Volume 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III; (1992) https://doi.org/10.1117/12.130927
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

Many computational schemes in linear algebra can be studied from the point of view of (discrete) time-varying linear systems theory. For example, the operation `multiplication of a vector by an upper triangular matrix' can be represented by a computational scheme (or model) that acts on the entries of the vector sequentially. The number of intermediate quantities (`states') that are needed in the computations is a measure of the complexity of the model. If the matrix is large but its complexity is low, then not only multiplication, but also other operations such as inversion and factorization, can be carried out efficiently using the model rather than the original matrix. In the present paper we discuss a number of techniques in time-varying system theory that can be used to capture a given matrix into such a computational network.

Citation Download Citation

Alle-Jan van der Veen and Patrick W. Dewilde "Time-varying computational networks: realization, lossless embedding, and structural factorization", Proc. SPIE 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III, (30 November 1992); https://doi.org/10.1117/12.130927

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