Gaussian Activation Functions Using Markov Chains  

Oleh:

Card, H. C. ; McNeill, D. K.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 6 (2002), page 1465-1471.
Topik: markov chain; gaussian activation; markov chains

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.7A Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We extend, in two major ways, earlier work in which sigmoidal neural non linearities 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 neural transfer functions employed in Gaussian mixture models. The hardware advantages of (non linear) stochastic signal processing (SSP) may be offset by increased processing time ; we quantify these issues. The ability to realize accurate Gaussian activation functions for neurons in pulsed digital networks using simple hardware with stochastic signals is also analyzed quantitatively.

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