Minimizing interference in satellite communications using transiently chaotic neural networks
Computers & Mathematics with Applications
Optimal matching by the transiently chaotic neural network
Applied Soft Computing
A two-phase chaotic neural network algorithm for channel assignment in cellular systems
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
On a chaotic neural network with decaying chaotic noise
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Algorithm analysis and application based on chaotic neural network for cellular channel assignment
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Comparative study of chaotic neural networks with different models of chaotic noise
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Chaotic cellular neural networks with negative self-feedback
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
| Hi-index | 0.00 |
By adding chaotic noise to each neuron of the discrete-time continuous-output Hopfield neural network (HNN) and gradually reducing the noise, a chaotic neural network is proposed so that it is initially chaotic but eventually convergent, and, thus, has richer and more flexible dynamics compared to the HNN. The proposed network is applied to the traveling salesman problem (TSP) and that results are highly satisfactory. That is, the transient chaos enables the network to escape from local energy minima and to find global minima in 100% of the simulations for four-city and ten-city TSPs, as well as near-optimal solutions in most of runs for a 48-city TSP.