Title :
Multiply descent cost competitive neural networks with cooperation and categorization
Author :
Matsuyama, Yasuo
Author_Institution :
Dept. of Comput. & Inf. Sci., Ibaraki Univ., Japan
fDate :
30 Sep-1 Oct 1991
Abstract :
Generalized competitive learning algorithms are described. These algorithms comprise competition handicaps, cooperation and multiply descent cost property. Applications are made on single processing and combinatorial optimizations. Parallel computation of the algorithms presented is discussed
Keywords :
combinatorial mathematics; learning (artificial intelligence); neural nets; signal processing; combinatorial optimizations; competition handicaps; competitive learning algorithms; cooperation; multiply descent cost property; neural networks; single processing; Application software; Computational Intelligence Society; Computer networks; Cost function; Information science; Neural networks; Neurons; Signal processing algorithms; Training data;
Conference_Titel :
Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
Conference_Location :
Princeton, NJ
Print_ISBN :
0-7803-0118-8
DOI :
10.1109/NNSP.1991.239527
