DocumentCode
2656982
Title
An optimal dimension expansion procedure for obtaining linearly separable subsets
Author
Tseng, Yuen-Hsien ; Wu, Ja-Ling
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fYear
1991
fDate
18-21 Nov 1991
Firstpage
2461
Abstract
The authors study the necessary and sufficient condition for linearly separable subsets and then propose an optimal dimension expansion procedure that makes any mapping to be performed by perceptrons learnable by an error-correction procedure. For n -bit parity check problems, it is shown that only one additional dimension is augmented to make them solvable by single-layer perceptrons. Other applications such as for decoding error-correcting codes are also considered
Keywords
decoding; error correction; learning systems; neural nets; set theory; decoding; error-correcting codes; error-correction; learning systems; linearly separable subsets; necessary and sufficient condition; neural nets; optimal dimension expansion procedure; perceptrons; set theory; Computer errors; Computer science; Decoding; Digital circuits; Equations; Error correction codes; Modems; Parity check codes; Sufficient conditions;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170758
Filename
170758
Link To Document