Review of Differential Threshold Gate Implementations

ABSTRACT This paper reviews differential implementations of threshold logic gates, detailing two classes of solutions: capacitive (floating gate and switched capacitor), and conductance/current. KEY WORDS Differential gates, threshold logic, perceptron, VLSI, neural network 1. Introduction Research on neural networks (NNs) goes back sixty years. The seminal year for the development of the “science of mind” was 1943 when the article A Logical Calculus of the Ideas Immanent in Nervous Activity by McCulloch and Pitts was published [24]. They introduced the first mathematical model of a neuron, the perceptron, or threshold logic (TL) gate (TLG): f (x 1, K, x n ) = sgn ( ∑ n =1 −θ )i wi xi (1) Capacitive TLGs can be classified into two major groups: where w i is the synaptic weight associated to x i , θ is the threshold , and n is the fan-in of the TLG. The general belief that a neuron is a TLG, which fires when some variable reaches a threshold , can be questionable. That is why, the TLG model has been tested on a spike train generated by the Hodgkin-Huxley model (a precise four-dimensional neuron model) with a stochastic input [18]. The result was that the threshold model correctly predicts nearly 90% of the spikes,

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