• 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