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Bradley D. Brown, Howard C. Card, "Stochastic Neural Computation II: Soft Competitive Learning," IEEE Transactions on Computers, vol. 50, no. 9, pp. 906920, September, 2001.  
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@article{ 10.1109/12.954506, author = {Bradley D. Brown and Howard C. Card}, title = {Stochastic Neural Computation II: Soft Competitive Learning}, journal ={IEEE Transactions on Computers}, volume = {50}, number = {9}, issn = {00189340}, year = {2001}, pages = {906920}, doi = {http://doi.ieeecomputersociety.org/10.1109/12.954506}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Computers TI  Stochastic Neural Computation II: Soft Competitive Learning IS  9 SN  00189340 SP906 EP920 EPD  906920 A1  Bradley D. Brown, A1  Howard C. Card, PY  2001 KW  Pulsed neural networks KW  stochastic arithmetic KW  competitive learning. VL  50 JA  IEEE Transactions on Computers ER   
Abstract—An investigation has been made into the use of stochastic arithmetic to implement an artificial neural network solution to a typical pattern recognition application. Optical character recognition is performed on very noisy characters in the E13B MICR font. The artificial neural network is composed of two layers, the first layer being a set of soft competitive learning subnetworks and the second a set of fully connected linear output neurons. The observed number of clock cycles in the stochastic case represents an order of magnitude improvement over the floatingpoint implementation assuming clock frequency parity. Network generalization capabilities were also compared based on the network squared error as a function of the amount of noise added to the input patterns. The stochastic network maintains a squared error within 10 percent of that of the floatingpoint implementation for a wide range of noise levels.
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