Title :
Stochastic resonance neural network and its performance
Author :
Nobori, Tatsuhiko ; Matsui, Nobuyuki
Author_Institution :
Dept. of Comput. Eng., Himeji Inst. of Technol., Hyogo, Japan
Abstract :
We describe the results of computer simulations of the dynamical behavior of a neural network model based on BP learning incorporated with stochastic resonance (SR neural network). This model is effective in solving the XOR problem, as reported in our previous work. This network is a small scale network for practical engineering. In this study, therefore we apply 4 bits parity problem and investigate learning abilities in the enhanced network to establish our SR method. From the results of experiments, we see the learning abilities of our network is improve more than the limited abilities of the traditional BP learning network. We also observe the stochastic resonance in our network
Keywords :
backpropagation; neural nets; resonance; stochastic processes; virtual machines; 4 bits parity problem; BP learning; SR neural network; XOR problem; backpropagation; computer simulations; learning abilities; stochastic resonance neural network; Biological neural networks; Computer networks; Information processing; Neural networks; Neurons; Nonlinear systems; Signal to noise ratio; Stochastic resonance; Strontium; Switches;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.857867