Bifurcation Nonlinear Dynamics Neural by Daneshyari Moayed (5 results)

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Taschenbuch. Condition: Neu. Bifurcation and Nonlinear Dynamics in Neural Network | Theory and Application | Moayed Daneshyari | Taschenbuch | 96 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783838365886 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Language: English
Published by LAP LAMBERT Academic Publishing Mai 2010, 2010
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nonlinear dynamics play an important role on biological livings, including biological neural systems. Researchers have shown that nonlinear dynamics and chaos exist in several levels of neural systems from micro to macro levels. This is a strong motivation for the addition of nonlinear dynamics and chaos into neural networks. In this book, a new type of neural network is introduced based on the nonlinear dynamics and chaos. Bifurcation behavior of the neural network shows that the state of the neurons will move chaotically among the stored states of the network but finally, by decreasing the degree of chaos, settles down into a proper state. Therefore this new type of neural network with chaotic dynamics is able to search the state space and seeks the points far away from equilibrium points. We also find that increasing the memory capacity of the neural network is one of the consequences of adding the nonlinearity into it. This network can also be used for pattern recognition, classification, and optimization. 96 pp. Englisch.…

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Nonlinear dynamics play an important role on biological livings, including biological neural systems. Researchers have shown that nonlinear dynamics and chaos exist in several levels of neural systems from micro to macro levels. This is a strong motivation for the addition of nonlinear dynamics and chaos into neural networks. In this book, a new type of neural network is introduced based on the nonlinear dynamics and chaos. Bifurcation behavior of the neural network shows that the state of the neurons will move chaotically among the stored states of the network but finally, by decreasing the degree of chaos, settles down into a proper state. Therefore this new type of neural network with chaotic dynamics is able to search the state space and seeks the points far away from equilibrium points. We also find that increasing the memory capacity of the neural network is one of the consequences of adding the nonlinearity into it. This network can also be used for pattern recognition, classification, and optimization.…

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Daneshyari MoayedMoayed Daneshyari is currently Assistant Professor at Elizabeth City State University where he joined in 2008. His educations are in electrical engineering, biomedical engineering, physics and computer engineering. H.…

Language: English
Published by LAP LAMBERT Academic Publishing Mai 2010, 2010
- Softcover
- Print on Demand
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Nonlinear dynamics play an important role on biological livings, including biological neural systems. Researchers have shown that nonlinear dynamics and chaos exist in several levels of neural systems from micro to macro levels. This is a strong motivation for the addition of nonlinear dynamics and chaos into neural networks. In this book, a new type of neural network is introduced based on the nonlinear dynamics and chaos. Bifurcation behavior of the neural network shows that the state of the neurons will move chaotically among the stored states of the network but finally, by decreasing the degree of chaos, settles down into a proper state. Therefore this new type of neural network with chaotic dynamics is able to search the state space and seeks the points far away from equilibrium points. We also find that increasing the memory capacity of the neural network is one of the consequences of adding the nonlinearity into it. This network can also be used for pattern recognition, classification, and optimization.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch.…