Estimation and Control in the VLSI Era
STANFORD UNIV CA DEPT OF ELECTRICAL ENGINEERING
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The theme of this lecture is that the availability of very high density integrated circuits will be changing our approach and emphasis to several problems in estimation and control. For example, the minimality of realizations will be less significant than their modularity, local interconnectedness, area time complexity measures, etc. Similarly, good algorithms for serial processing may be poor candidates for parallel implementation. While it is hard for me in mid-August to predict exactly what I shall say in the lecture in mid-December, I think it might be useful to provide in written form some of the background material on which a good part of may talk will be based. Thus, at this meeting at least, I plan to illustrate the above points by several examples, including 1 description of a parallel architecture for the measurement update step in triangular array form of the Kalman filter 2 development of the Schur algorithm as a better candidate than the Levinson algorithm for VLSI implementation of Toeplitz equation solvers 3 comparison of the Berlekamp-Massey-Rissanen and Lanczos algorithms in the problems of partial realization and of the decoding of BCH codes and 4 development of minimal, but pipelined and orthogonally-cascaded, implementations of time-invariant, finite-dimensional ARMA systems.
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