Gaussian activation functions using Markov chains

We extend, in two major ways, earlier work in which sigmoidal neural nonlinearities were implemented using stochastic counters. 1) We define the signal to noise limitations of unipolar and bipolar stochastic arithmetic and signal processing. 2) We generalize the use of stochastic counters to include...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2002-11, Vol.13 (6), p.1465-1471
Hauptverfasser:	Card, H.C., McNeill, D.K.
Format:	Artikel
Sprache:	eng
Schlagworte:	Arithmetic Counting circuits Gaussian Gaussian noise Hardware Mathematical models Neural network hardware Neural networks Neurons Nonlinearity Signal analysis Signal processing Stochastic processes Stochastic resonance Stochasticity Transfer functions
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