Pattern stability on complex-valued associative memory by local iterative learning scheme

2012 ◽  
Author(s):  
Hiroki Yamamoto ◽  
Teijiro Isokawa ◽  
Haruhiko Nishimura ◽  
Naotake Kamiura ◽  
Nobuyuki Matsui
Keyword(s):  
Associative Memory ◽  
Iterative Learning ◽  
Learning Scheme ◽  
Pattern Stability ◽  
Complex Valued

Complex-valued multistate neural associative memory

1996 ◽  
Vol 7 (6) ◽  
pp. 1491-1496 ◽  
Author(s):  
S. Jankowski ◽  
A. Lozowski ◽  
J.M. Zurada
Keyword(s):  
Associative Memory ◽  
Complex Valued

Evaluation Model of Bridges Health State Based on DHNN

2014 ◽  
Vol 1079-1080 ◽  
pp. 207-211
Author(s):  
Min He ◽  
Rui Guang Hu ◽  
Shi Le ◽  
Liang Chen
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Evaluation Model ◽  
Memory Capacity ◽  
Iterative Learning ◽  
Health Evaluation ◽  
Health State ◽  
Outer Product ◽  
State Evaluation ◽  
Product Method

Inthis paper, according to the more important ten evaluation indicators, the fourgrades ideal evaluation is established corresponding to the level of healthstate of bridges. Combined with associative memory capacity of discreteHopfield neural networks, a new health state evaluation of bridges ispresented. Five bridges is evaluated by the model, the network connectionweights is obtained by iterative learning using the outer product method. Thesimulation results shows that the health evaluation model can evaluate thehealth state of bridges fast, accurately and intuitively.

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