DocumentCode
288595
Title
O(n) depth-2 binary addition with feedforward neural nets
Author
Vassiliadis, S. ; Bertels, K. ; Pechanek, G.G.
Author_Institution
IBM Corp., Austin, TX, USA
Volume
3
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
1381
Abstract
In this paper we investigate the reduction of the size of depth-2 feedforward neural networks performing binary addition and related functions. We suggest that 2-1 binary n-bit addition and some related functions can be computed in a depth-2 network of size O(n) with maximum fan-in of 2n+1. Furthermore, we show, if both input polarities are available, that the comparison can be computed in a depth-1 network of size O(1) also with maximum fan-in of 2n+1
Keywords
Boolean functions; computational complexity; feedforward neural nets; Boolean function; depth-1 network; depth-2 binary addition; depth-2 network; feedforward neural nets; input polarities; Boolean functions; Circuits; Computer networks; Feedforward neural networks; Microelectronics; Neural networks; Neurons; Polynomials; Reduced instruction set computing; Size measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374487
Filename
374487
Link To Document