Solving ability of Hopfield neural network with chaotic noise and burst noise for quadratic assignment problem

Proceedings - IEEE International Symposium on Circuits and Systems

Volumn 3, Issue , 2002, Pages 465-468

  Uwate, Yoko ^a   Nishio, Yoshifumi ^a   Ueta, Tetsushi ^a   Kawabe, Tohru ^b   Ikeguchi, Tohru ^c  

^a UNIVERSITY OF TOKUSHIMA   (Japan)

^b UNIVERSITY OF TSUKUBA   (Japan)

^c SAITAMA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CHAOS THEORY; COMBINATORIAL MATHEMATICS; COMPUTER SIMULATION; MATHEMATICAL MODELS; OPTIMIZATION; SPURIOUS SIGNAL NOISE;

CHAOS NOISE; GILBERT MODEL; QUADRATIC ASSIGNMENT PROBLEM;

NEURAL NETWORKS;

EID: 0036287607     PISSN: 02714310     EISSN: None     Source Type: Journal    
DOI: 10.1109/ISCAS.2002.1010261     Document Type: Article

References (9)

1. Neurons with graded response have collective computational properties like those of two-state neurons
2. Effects of chaotic noise on the performance of a neural network model
3. An analysis on adding effects of nonlinear dynamics for combinatorial optimization
4. Comparison between chaotic noise and burst noise on solving ability of Hopfield neural network
5. Hopfield neural network with various burst noise for TSP
6. Solving ability of the Hopfield NN with burst noise
7. An optimization method for quadratic assignment problems by chaotic dynamics and its characterization by Lyapunov dimensions
8. QAPLIB - A quadratic assignment problem library