Global stability analysis in delayed Hopfield neural network models

2000 ◽  
Vol 13 (7) ◽  
pp. 745-753 ◽  
Author(s):  
Jiye Zhang ◽  
Xuesong Jin
Keyword(s):  
Neural Network ◽  
Stability Analysis ◽  
Global Stability ◽  
Network Models ◽  
Hopfield Neural Network ◽  
Neural Network Models ◽  
Global Stability Analysis

Pattern Matching Synthesis As an Automated Approach to Mechanism Design

1989 ◽  
Author(s):  
D. A. Hoeltzel ◽  
W.-H. Chieng
Keyword(s):  
Neural Network ◽  
Mechanism Design ◽  
Pattern Matching ◽  
Network Models ◽  
Hopfield Neural Network ◽  
Neural Network Models ◽  
Knowledge Based ◽  
Synthesis Of Mechanisms ◽  
New Knowledge ◽  
Programming Techniques

Abstract A new knowledge-based approach for the synthesis of mechanisms, referred to as Pattern Matching Synthesis, has been developed based on committee machine and Hopfield neural network models of pattern matching applied to coupler curves. Computational tests performed on a dimensionally parameterized four bar mechanism have yielded 15 distinct coupler curve groups (patterns) from a total of 356 generated coupler curves. This innovative approach represents a first step toward the automation of mapping structure-to-function in mechanism design based on the application of artificial intelligence programming techniques.

Standard representation and unified stability analysis for dynamic artificial neural network models

2018 ◽  
Vol 98 ◽  
pp. 251-262 ◽  
Author(s):  
Kwang-Ki K. Kim ◽  
Ernesto Ríos Patrón ◽  
Richard D. Braatz
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stability Analysis ◽  
Network Models ◽  
Neural Network Models ◽  
Standard Representation ◽  
Artificial Neural ◽  
Artificial Neural Network Models

scholarly journals Stability Analysis of Neural Network Models in Engineering Design

2020 ◽  
Vol 9 (3) ◽  
pp. 1862-1866
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Stability Analysis ◽  
Engineering Design ◽  
Network Models ◽  
Control Problems ◽  
Neural Network Models ◽  
Optimization And Control ◽  
Efficient Criteria ◽  
And Control

In this paper neural networks applications in engineering design are discussed. The question for stability of their steady states is also considered. Some new efficient criteria are proposed. Since neural networks are relevant systems applied in various engineering design tasks, including many optimization and control problems, the results can be useful in design of such systems of diverse interest.

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