J1610102 A Numerical Simulation of Stochastic Resonance Using a Neural Network Model

2015 ◽  
Vol 2015 (0) ◽  
pp. _J1610102--_J1610102-
Author(s):  
Kohei KANBE ◽  
Masahiro OHKA
Keyword(s):  
Neural Network ◽  
Numerical Simulation ◽  
Stochastic Resonance ◽  
Network Model ◽  
Neural Network Model

MULTIPLE BIFURCATION ANALYSIS IN A NEURAL NETWORK MODEL WITH DELAYS

2006 ◽  
Vol 16 (10) ◽  
pp. 2903-2913 ◽  
Author(s):  
YUAN YUAN ◽  
JUNJIE WEI
Keyword(s):  
Neural Network ◽  
Numerical Simulation ◽  
Network Model ◽  
Neural Network Model ◽  
Bifurcation Theory ◽  
Center Manifold ◽  
Pitchfork Bifurcation ◽  
Center Manifold Theorem ◽  
Normal Form Method ◽  
Theoretical Results

A synchronized neural network model with delays is considered. The bifurcations arising from the zero root of the corresponding characteristic equation have been studied by employing the center manifold theorem, normal form method and bifurcation theory. It is shown that the system may exhibit transcritical/pitchfork bifurcation, or Bogdanov–Takens bifurcation. Some numerical simulation examples are given to justify the theoretical results.

Neural Network Model to Calculate the Creep Data Using Size

2017 ◽  
Vol 7 (8) ◽  
pp. 257
Author(s):  
Seetharam .K ◽  
Sharana Basava Gowda ◽  
. Varadaraj
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Software Engineering ◽  
Network Model ◽  
Neural Network Model ◽  
Software Metrics ◽  
Creep Data ◽  
Engineering Software ◽  
Function Points ◽  
Different Levels

In Software engineering software metrics play wide and deeper scope. Many projects fail because of risks in software engineering development[1]t. Among various risk factors creeping is also one factor. The paper discusses approximate volume of creeping requirements that occur after the completion of the nominal requirements phase. This is using software size measured in function points at four different levels. The major risk factors are depending both directly and indirectly associated with software size of development. Hence It is possible to predict risk due to creeping cause using size.

Sign in / Sign up

Export Citation Format

Share Document