By Thaddeus J. Kowalski
Publication by means of Kowalski, Thaddeus J.
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Additional info for An Artificial Intelligence Approach to VLSI Design
12), Ed = 3/4. 22). This design is also D- and E-optimal. The second relationship between a design and its dual concerns the generalized inverse of the information matrix. 25) is a generalized inverse of the informatiQIl matrix A by showing that AOA = A. 25). 8 Upper bounds for the average efficiency factor In the search for A-optimal designs it is useful to have available an upper bound for the average efficiency factor E as a measure against which to assess the scope for possible improvement.
5 n-Cyclic designs The cyclic designs considered in the previous sections have been obtained by a cyclic development of one or more initial blocks.
37). 1. 5) where E is the harmonic mean of the canonical efficiency factors or of the pairwise efficiency factors. 4) can be easily calculated. It is unnecessary with cyclic designs to use general, and time-consuming, eigenvalue and inverse subroutines. 1 Consider cyclic designs of size (11,4,4). The 330 distinct blocks can be set out in 30 cyclic sets. Under a permutation of the treatment labels each of these sets can be shown to be equivalent to one of four sets. 1. There are large differences between the efficiency factors of the designs.
An Artificial Intelligence Approach to VLSI Design by Thaddeus J. Kowalski
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