• DocumentCode
    394177
  • Title

    Single chip VLSI realization of a neural net for fast decision making functions

  • Author

    Stüpmann, Frank ; Rode, Steffen ; Geske, G.

  • Author_Institution
    Neurosystems GmbH, Rostock, Germany
  • Volume
    2
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    965
  • Abstract
    The newest results of a hardware realization of a neural net for fast decision making functions in real time are shown here. There is a digital micro core with any functions-proceeding of the learning and testing of the net, supervising of training process and computation of some calculations in pre- and post-processing. The decision-making function is a trainable integrated analog neural network structure. The circuit not only contains the reproduction path but also the learning on-chip. Learning patterns for the neural chip are provided in a memory unit. These patterns are automatically presented to the network. The process of weight change (i.e. learning) is fully integrated. The information processing speed from the input to the output of the chip is 2 μs in the reproduction process. The number of neurons integrated in the whole chip is 100 in the input layer, 60 in the hidden layer and 10 in the output layer. The back propagation algorithm is implemented in an analog circuit.
  • Keywords
    VLSI; image processing; learning (artificial intelligence); multilayer perceptrons; neural chips; real-time systems; decision making functions; image processing; memory unit; multilayer perceptron; neural net; real time systems; single chip VLSI; supervised learning; weight change; Circuit testing; Decision making; Information processing; Multilayer perceptrons; Neural network hardware; Neural networks; Neurons; Switches; Very large scale integration; Weight control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1198204
  • Filename
    1198204