Analog VLSI and neural systems
Analog VLSI and neural systems
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Handwritten digit recognition with a back-propagation network
Advances in neural information processing systems 2
Soft competitive adaptation: neural network learning algorithms based on fitting statistical mixtures
Analog Integrated Circuits and Signal Processing - Special issue: cellular neural networks and analog VLSI
Focal-Plane and Multiple Chip VLSI Approaches to CNNs
Analog Integrated Circuits and Signal Processing - Special issue: cellular neural networks and analog VLSI
Analog VLSI pulsed networks for perceptive processing
Pulsed neural networks
Stochastic Neural Computation I: Computational Elements
IEEE Transactions on Computers
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Reduction and Refinement Strategies for Probabilistic Analysis
PAPM-PROBMIV '02 Proceedings of the Second Joint International Workshop on Process Algebra and Probabilistic Methods, Performance Modeling and Verification
Wavelet descriptor of planar curves: theory and applications
IEEE Transactions on Image Processing
Neural network-based systems for handprint OCR applications
IEEE Transactions on Image Processing
The pandemonium system of reflective agents
IEEE Transactions on Neural Networks
A board system for high-speed image analysis and neural networks
IEEE Transactions on Neural Networks
Neural-network classifiers for recognizing totally unconstrained handwritten numerals
IEEE Transactions on Neural Networks
The DSFPN, a new neural network for optical character recognition
IEEE Transactions on Neural Networks
Decision-based neural networks with signal/image classification applications
IEEE Transactions on Neural Networks
Architecture and statistical model of a pulse-mode digital multilayer neural network
IEEE Transactions on Neural Networks
An efficient constrained training algorithm for feedforward networks
IEEE Transactions on Neural Networks
Stochastic Neural Computation I: Computational Elements
IEEE Transactions on Computers
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Reconfigurable Hardware Architecture for Compact and Efficient Stochastic Neuron
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Proceedings of the International Conference on Computer-Aided Design
Comparing the performance of stochastic simulation on GPUs and OpenMP
International Journal of Computational Science and Engineering
| Hi-index | 14.98 |
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 E-13B 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 floating-point 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 floating-point implementation for a wide range of noise levels.