Double synaptic weight neuron theory and its application


Autoria(s): Wang SJ; Chen X; Qin H; Li WJ; Bian Y
Data(s)

2005

Resumo

In this paper, a novel mathematical model of neuron-Double Synaptic Weight Neuron (DSWN)(l) is presented. The DSWN can simulate many kinds of neuron architectures, including Radial-Basis-Function (RBF), Hyper Sausage and Hyper Ellipsoid models, etc. Moreover, this new model has been implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. The flexibility of the DSWN has also been described in constructing neural networks. Based on the theory of Biomimetic Pattern Recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-II neurocomputer. In these two special cases, the result showed DSWN neural network had great potential in pattern recognition.

Identificador

http://ir.semi.ac.cn/handle/172111/8464

http://www.irgrid.ac.cn/handle/1471x/63762

Idioma(s)

英语

Fonte

Wang, SJ; Chen, X; Qin, H; Li, WJ; Bian, Y .Double synaptic weight neuron theory and its application ,ADVANCES IN NATURAL COMPUTATION,2005 ,PT 1 PROCEEDINGS 3610(0):264-272

Palavras-Chave #人工智能
Tipo

期刊论文