Switched Capacitor-Based Integrate-And-Fire Neural Network

  • D. Hajtáš
  • D. Ďuračková
  • G. Benyon-Tinker
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 5)


This article deals with an analog implementation of the functional parts of an Integrate-and-fire neural network. The designed parts would be used as leaf cells with automated layout generation for a complex Integrate-and-fire neural network with built-in analog learning and weight storage. The most important cell is the synapse, which includes a postsynaptic forming block, learning and weight storage, which makes it possible to give individual output characteristics to each synapse in a complete neural network. This approach is conceptually close to its biological counterpart. The design uses a switched capacitor technique to achieve a significant reduction in silicon area.


Dendritic Tree Clock Signal Switch Capacitor Current Comparator Switch Capacitor Circuit 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • D. Hajtáš
    • 1
  • D. Ďuračková
    • 1
  • G. Benyon-Tinker
    • 2
  1. 1.dept. of MicroelectronicsSlovak University of TechnologyBratislavaSlovakia
  2. 2.School of Design, Engineering and ComputingBournemouth UniversityBournemouthUK

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