DocumentCode :
3009450
Title :
Classification using single neuron
Author :
Yadav, R.N. ; Singh, V. ; Kalra, Prem
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., Kanpur, India
fYear :
2003
fDate :
21-24 Aug. 2003
Firstpage :
124
Lastpage :
129
Abstract :
Since the neuron is the basic information processing unit of the brain, the ANN have played a great role in the study of the brain. Because of the complexity and less understanding about the biological neurons, many scientists and researchers have given various architecture for it. Experimental studies in the area of neuroscience has proven that the response of a biological neuron appears random and the predicted results can be obtained in many ways. We have presented some new models of the artificial neuron that can be used to solve the various bench-mark problems in a very simple and systematic manner.
Keywords :
brain; neural nets; neurophysiology; pattern classification; ANN; SPRB; Sigma-Pi-Pi; Sigma-Pi-Sigma; artificial neuron; bench-mark problem; biological neuron; brain information processing unit; neuron model; neuroscience; single neuron classification; Artificial neural networks; Biological system modeling; Biology computing; Computer architecture; Humans; Information processing; Least squares approximation; Neurons; Neuroscience; Systematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Informatics, 2003. INDIN 2003. Proceedings. IEEE International Conference on
Print_ISBN :
0-7803-8200-5
Type :
conf
DOI :
10.1109/INDIN.2003.1300258
Filename :
1300258
Link To Document :
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