DocumentCode
1905720
Title
A serial complexity measure of neural networks
Author
Sipper, Moshe
Author_Institution
Dept. of Comput. Sci., Tel Aviv Univ., Israel
fYear
1993
fDate
1993
Firstpage
962
Abstract
The most common methodology of neural network analysis is that of simulation since as of yet there is no common formal framework. Towards this end, one measure of serial algorithms is adopted, i.e., that of serial computational complexity. It is applied to the analysis of neural networks. Various networks are analyzed and their complexity is derived, thus providing insight as to their computational requirements
Keywords
computational complexity; neural nets; computational complexity; computational requirements; neural networks; serial algorithms; serial complexity measure; Algorithm design and analysis; Computational complexity; Computational modeling; Computer networks; Computer science; Electronic mail; Hamming distance; Neural networks; Neurons; Read-write memory;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298687
Filename
298687
Link To Document