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《BEIJING BIOMEDICAL ENGINEERING》 1997-02
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The Biology-Based Theoretical Frame For the NeuralNetwork-Neuron Model

Ouyang Kai,Zhou Rui, Liu Weifang (Dept ,of BME Capital University of Medical Saiences, Beijing 100054)  
In order to manifest the richness and variety of artificial neural networks (ANN), their intelligent behavior, and to develop advanced applications of ANN. it is necessary to build theoretical frame for the ANN Here presented is the first part of the fiame, which includes the following three parts: neuron model, plasticity of synapses and their leaening algorithms, and the architecture of the neural network. The neuron model is composed of nine features based on neurophysiology, including: ( 1 ) spatial summation effect (2) tempofal summation effect (3) the characteristics of the threshold; (4) non-respond duration; (5) adaptability; (6) excitation and characteristics; (7) delay: (8) characteristics of the output. (9) characteristics of conductivity. These features are obtained by long-term physiological experiments, or by H-H equation with computer simuiation which we carried out The neuron models, which have these nine neuron properties, are not convenient for mathematical analysis. In some cases. some characters of them are not important,such as conductivity, adaptability, etc. while some other characters (spatal summation effect, output character, etc.) are more important. If we review the popular ANN. models with the nine features, we can find that all of them are within these features. We used these features in practice and simulation research, satisfactory results were obtained, such as associated memory and data compression in ECG.
【Fund】: 国家自然科学基金 863计划、攀登计划资助
【CateGory Index】: R318
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