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ICANN ’93 pp 43-46 | Cite as

Neurobiological Modelling and Structured Neural Networks

  • B. Brückner
  • W. Zander

Abstract

We are presenting a coupled modelling concept which is suitable to reproduce sensory systems in a plausible way. The idea is to connect a biological relevant Neural Network as a filter with a structured formal Neural Network to classify the filtered data. Because the biological filter is very flexible and self organized it has the capacity to make segmentation and feature extraction of input data like a sensory pathway. So, temporal processes can be represented in a sequence of prefiltered segments. The produced time sequences are suited for the analysis by a multi-stage construction of the classification network, which has a modified Hypermap structure. The presented system is succesfully used for speech recognition of different subjects.

Keywords

Sensory Node Feature Extraction Input Vector Speech Recognition Speech Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 1993

Authors and Affiliations

  • B. Brückner
    • 1
  • W. Zander
    • 1
  1. 1.Department acoustics, learning, speechInstitute of Neurobiology MagdeburgMagdeburgGermany

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