Accession Number : ADD012271
Title : A Linear Algorithm for Non-Linear Interpolation for Computer Aided Designs.
Descriptive Note : Patent Application,
Corporate Author : DEPARTMENT OF THE ARMY WASHINGTON DC
Personal Author(s) : Rubin,Stuart H
Report Date : 04 Apr 1986
Pagination or Media Count : 14
Abstract : This invention (patent application) relates to computer aided intelligence design and, more particularly, to an artificial intelligence program for use wherever very fast, interpolating learning algorithms are required. The linear algorithm of the present invention is a deterministic algorithm, which permits a user to store any MP2D run, and retrieve any of the 'run's' statistics, inclusive of 'run time'. When written in Fortran, it is such a 'learning base' which permits a user to predict such statistics in 0 (N) time -- i.e., linear time, along with a measurement of reliability, and for any or all of the maximum 961 runs permitted with the MP2D computer. Although, in a preferred embodiment of the invention, a cell counter interface to the MP2D input was employed of a 0 (N**2) process, in operation this would still be considered as a O (N) process with but little loss in performance if some 3,000 cells were exceeded -- and, for the reason that any standby on a computer just to count cells does not establish any substantial problem as it takes many orders of magnitude more time to establish the existing MP2D input form (and, since the cell count is only performed once, never for the 're-run' modifications). As will be seen from the description that follows, the linear algorithm of the invention will be seen to operate utilizing three of the basic statistics from the MP2D input base -- namely, a) the number of cells; b) the number of basic wires required; and c) the estimated placement complexity.
Descriptors : *PATENT APPLICATIONS, *ALGORITHMS, *COMPUTER AIDED DESIGN, ARTIFICIAL INTELLIGENCE, CELLS, COUNTING METHODS, DETERMINANTS(MATHEMATICS), EMPLACEMENT, ESTIMATES, FORTRAN, INTERPOLATION, COMPUTER PROGRAMS, LINEARITY, INVENTIONS, LEARNING, MEASUREMENT, NONLINEAR SYSTEMS, RELIABILITY, STATISTICS, TIME, WIRE
Subject Categories : Computer Programming and Software
Distribution Statement : APPROVED FOR PUBLIC RELEASE