Solving combinatorial optimization problem is one of the im-portant applications of neural network (abbr. NN). However, the solutions are often trapped into a local minimum and do not reach the global minimum. In order to avoid this critical problem, several people proposed the method adding some kinds of noise. In this study, we consider torus noise generated by the sine circle map for the Hopfield NN. By computer simula-tions, solving abilities of Hopfield NN for quadratic assign-ment problem (QAP) with various kinds of noises based on the torus noise are investigated. 1
Optimization plays a significant role in almost every field of applied sciences (e.g., signal proces...
[[abstract]]The Hopfield neural network (HNN) is one major neural network (NN) for solving optimizat...
The neural network is a calculation model which can replicate some functions of human brain. In addi...
Combinatorial optimization problems can be solved with the Hopfield Neural Network. If we choose con...
Abstract — One of the applications of neural network is solving combinatorial optimization problems....
Abstract—Solving combinatorial optimization problems is one of the important applications of neural ...
In this paper, performance of chaos and burst noises injected to the Hopfield Neural Network for qua...
In this paper, we investigate the solving ability of Hop-field neural network with iterative simulat...
Although it would be possible to solve combinatorial op-timization problems with a huge number of el...
Abstract In our past study, the solving ability of the Hopeld Neural Network with noise for quadrat...
Neural networks can be successfully applied to solving certain types of combinatorial optimization p...
Abstract—Channel assignment problem in cellular communication is a difficult combinatorial optimizat...
After more than a decade of research, there now exist several neural-network techniques for solving ...
Abstract. In the use of Hopfield networks to solve optimization problems, a critical problem is the ...
Abstract: Multi-modal optimisation problems are characterised by the presence of either local sub-op...
Optimization plays a significant role in almost every field of applied sciences (e.g., signal proces...
[[abstract]]The Hopfield neural network (HNN) is one major neural network (NN) for solving optimizat...
The neural network is a calculation model which can replicate some functions of human brain. In addi...
Combinatorial optimization problems can be solved with the Hopfield Neural Network. If we choose con...
Abstract — One of the applications of neural network is solving combinatorial optimization problems....
Abstract—Solving combinatorial optimization problems is one of the important applications of neural ...
In this paper, performance of chaos and burst noises injected to the Hopfield Neural Network for qua...
In this paper, we investigate the solving ability of Hop-field neural network with iterative simulat...
Although it would be possible to solve combinatorial op-timization problems with a huge number of el...
Abstract In our past study, the solving ability of the Hopeld Neural Network with noise for quadrat...
Neural networks can be successfully applied to solving certain types of combinatorial optimization p...
Abstract—Channel assignment problem in cellular communication is a difficult combinatorial optimizat...
After more than a decade of research, there now exist several neural-network techniques for solving ...
Abstract. In the use of Hopfield networks to solve optimization problems, a critical problem is the ...
Abstract: Multi-modal optimisation problems are characterised by the presence of either local sub-op...
Optimization plays a significant role in almost every field of applied sciences (e.g., signal proces...
[[abstract]]The Hopfield neural network (HNN) is one major neural network (NN) for solving optimizat...
The neural network is a calculation model which can replicate some functions of human brain. In addi...