On using parametric string distances and vector quantization in designing syntactic pattern recognition systems

2002 ◽  
Author(s):  
B.J. Oommen ◽  
R.K.S. Loke
Keyword(s):  
Pattern Recognition ◽  
Vector Quantization ◽  
Syntactic Pattern Recognition ◽  
Syntactic Pattern ◽  
Pattern Recognition Systems ◽  
Recognition Systems

Control Chart Pattern Recognition Using Combinations of Multi-Layer Perceptrons and Learning-Vector-Quantization Neural Networks

1993 ◽  
Vol 207 (2) ◽  
pp. 113-118 ◽  
Author(s):  
D T Pham ◽  
E Oztemel
Keyword(s):  
Pattern Recognition ◽  
Control Chart ◽  
Vector Quantization ◽  
Learning Vector Quantization ◽  
Composite Pattern ◽  
Pattern Recognition Systems ◽  
Network Modules ◽  
Recognition Systems ◽  
Control Chart Pattern ◽  
Chart Patterns

Pattern recognition systems made up of independent multi-layer perceptrons and learning-vector-quantization neural network modules have been developed for classifying control chart patterns. These composite pattern recognition systems have better classification capabilities than their individual modules. The paper describes the structures of these pattern recognition systems and the results obtained on using them.

Sign in / Sign up

Export Citation Format

Share Document