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An emulator for biologically-inspired neural networks



Institute of Electrical and Electronics Engineers -IEEE-:
IJCNN '93. International Joint Conference on Neural Networks. Proceedings
Piscataway/N.J., 1993
ISBN: 0-7803-1421-2
International Joint Conference on Neural Networks <1993, Nagoya>
Fraunhofer IMS ()
adaption; adaptive signal processing; anwenderspezifische integrierte Schaltung; ASIC; Biokybernetik; biological cybernetics; biological neural network; Echtzeitbetrieb; Emulation; hardware; neural emulator; neural hardware; neuronales Netzwerk; parallel computer; Parallelrechnersystem; real-time system; Signalverzögerung; system design; Systementwurf

This work presents an emulator that has been developed for real-time algorithm and architecture exploration and verification of biologically-inspired neural networks. It can implement a wide range of user-defined neural network types and neuron models. The most complex neuron model is represented by a "biological" neuron that incorporates not only synaptic weighting, postsynaptic summation, static threshold, and saturation, but also other parameters, such as synaptic time delays, neuron gain, computation of membrane potential, and dynamic thresholding, all variable and learnable. For this purpose, a special custom-made CMOS chip has been developed, fabricated, and tested. The chip has been used to build a neural emulator in a form of neural grid array that can interface sensors, actuators, and a host computer.