Suchergebnisse

The 54th IEEE International Midwest Symposium on Circuits and Systems, Korea August 7-10, 2011, CDROM, pp.1-4. ; This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted. ; Constant weight codewords, in which the number of 1's is constant, are essential to combinatorial computing. For example, it is often useful to generate all subsets of a set with a fixed number of elements. In this paper, we show an efficient circuit that converts a constant weight codeword into a unique index of that codeword. This circuit is a necessary part of a circuit that uses constant weight codewords to transmit data on and off chip. Our circuit is based on the combinatorial number system in which the digits are binomial coefficients n r. Experimental results show the efficiency of our design.

RM-2007, Oslo, Norway, May 16, 2007. ; This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted. ; decomposition.

33rd International Symposium on Multiple-Valued Logic, Tokyo, May 16-19, 2003. pp.383-390. ; This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted. ; We consider the path length in decision diagrams for multiple-valued functions. This is an important measure of a decision diagram, since this models the time needed to evaluate the function. We consider the path length in decision diagrams for multiple-valued functions. This is an important measure of a decision diagram, since this models the time needed to evaluate the function. We consider the path length in decision diagrams for multiple-valued functions. This is an important measure of a decision diagram, since this models the time needed to evaluate the function. We consider the path length in decision diagrams for multiple-valued functions. This is an important measure of a decision diagram, since this models the time needed to evaluate the function.

International Symposium on New Paradigm VLSI Computing, Sendai, Japan, Dec. 12-14, 2002, pp.31-36. ; This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted. ; This paper focuses on the average path length (APL) of BDD's for switching functions. APL is a metric for the time it takes to evaluate the function by a computer program. We derive the APL for the AND, OR, parity, carry-out, comparison, threshold symmetric, and majority functions. We also consider the average of the APL for various classes of functions, including symmetric, threshold symmetric, and majority functions. We also consider the average of the APL for various classes of functions, including symmetric, threshold symmetric, and unate cascade. For symmetric functions, we show the average APL is close to the maxium path length, n, the number of variables.

The 12th Workshop on Synthesis And System Integration of Mixed Information technologies (SASIMI2004), Oct. 18-19, 2004, Kanazawa, Japan, pp.422-429. ; This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted. ; The availability of large, inexpensive memory has made it possible to realize numerical functions, such as the reciprocal, square root, and trigonometric functions, using a look-up table. This is much faster than by software. However, a naive look-up method requires unreasonably large memory. In this paper, we show the use of a look-up table (LUT) cascade to realize a piecewise linear approximation to the given function. Our approach yields memory of reasonable size and significant accuracy.