Title :
Characteristics of associative chaotic neural networks with weighted pattern storage-a pattern is stored stronger than others
Author :
Adachi, Masakazu ; Aihara, Kazuyuki
Author_Institution :
Dept. of Electron. Eng., Tokyo Denki Univ., Japan
Abstract :
Associative chaotic neural networks with weighted pattern storage are studied. Values of the synaptic weights of conventional associative neural networks are determined by an auto-associative matrix. On the other hand, in this paper, we use a weighted auto-associative matrix in order to store a pattern that is stronger than the other stored patterns. Retrieval characteristics and dynamical properties of associative chaotic neural networks with this weighted auto-associative matrix are numerically analysed. As a result, the network retrieves the strongly stored pattern more frequently than other stored patterns, even in the case where the dynamics of the network is chaotic
Keywords :
associative processing; chaos; content-addressable storage; information retrieval; neural nets; associative chaotic neural networks; chaotic dynamics; dynamical properties; numerically analysis; pattern retrieval characteristics; strongly stored pattern; synaptic weights; weighted auto-associative matrix; weighted pattern storage; Biological neural networks; Brain modeling; Chaos; Convergence; Educational institutions; Neural networks; Neurofeedback; Neurons; Paper technology; Physics;
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
DOI :
10.1109/ICONIP.1999.844677
