An adaptive VLSI neural network chip
R.U. Zaman, Donald C. Wunsch · 2002
Presents an adaptive neural network, which uses multiplying-digital-to-analog converters (MDACs) as synaptic weights. The chip takes advantage of digital processing to learn weights, but retains the parallel asynchronous behavior of analog systems, since part of the neuron functions are analog. The authors use MDAC units of 6 bit accuracy for this chip. Hebbian learning is employed, which is very attractive for electronic neural networks since it only uses local information in adapting weights.>