A Neural Network Approach to Real-Time Discrete Tomography

2006 ◽  
pp. 389-403 ◽  
Author(s):  
K. J. Batenburg ◽  
W. A. Kosters
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Network Approach ◽  
Discrete Tomography ◽  
Neural Network Approach

A NEURAL NETWORK APPROACH TO REAL-TIME PATTERN RECOGNITION

2001 ◽  
Vol 15 (06) ◽  
pp. 937-947 ◽  
Author(s):  
JINWEN MA
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Real Time ◽  
Error Probability ◽  
Time Constraints ◽  
Network Approach ◽  
Noisy Environment ◽  
Neural Network Approach ◽  
Time Pattern ◽  
Perceptive Field

This paper presents a new neural network approach to real-time pattern recognition on a given set of binary (or bipolar) sample patterns. The perceptive neuron of a binary pattern is defined and constructed as a binary neuron with a neighborhood perceptive field. Letting its hidden units be the respective perceptive neurons of the patterns, a three-layer forward neural network is constructed to recognize these patterns with minimum error probability in a noisy environment. The theoretical and simulation analyses show that the network is effective for pattern recognition and can be under strict real-time constraints.

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