350 rub
Journal Neurocomputers №7 for 2010 г.
Article in number:
Neural network with associative and fading memory as model of viscoelastic media
Keywords:
viscoelastic medium
Maxwell-s
Voigt-Kelvin-s and Jeffreуs - viscoelastic elements
viscoelastic elements with assotiative memory
relaxation spectrum
relax matrix
assotiative memory model
nonlinear integro-differential equation
nonlinear dynamic neural network
synaptic links
long-term memory
short-term memory
training with the teacher
Authors:
Yu.А. Basistov, Yu.G. Janovsky
Abstract:
The dynamic model of the nonlinear viscoelastic element possessing associative and fading memory is offered. The model generalises known viscoelastic elements of Maxwell, Jeffrey and Voigt-Kelvin. The nonlinear mathematical model for simulating behavior of complex heterogeneous viscoelastic media is synthesised. The model consists of nonlinear viscoelastic elements with fading and associative memory, and synaptic connection between them in the form of integral Volterra operators. It is established that the offered model can be realized on a nonlinear dynamic neural network with associative and fading memory. It is shown that the known neural network of Hopfield is a special case of the offered model. The theorem of stability of the offered dynamic model is resulted. Identification of our model is made by algorithm "training with the teacher" and consists in a choice of elements relaxation matrix by mean of a minimum root-mean-square error between result of simulating and the required. The diagonal relaxation matrix is squares a relaxation times of separate viscoelastic elements. Other elements of this matrix characterize relaxation synaptic connection between viscoelastic elements. The model is realized in the form of the nonlinear integro-differential system equations. The integral part contains long-term memory of model, and a differential part - short-term memory.
Pages: 29-39
References
- Басистов Ю.А., Яновский Ю.Г. Нейродинамическая модель вязкоупругих сред с ассоциативной памятью // Доклады Академии наук (РАН). 2010. Т. 430. №4.С.494-497.
- Solowey D., Haley P.J. Neural Generalized Predictive Control. Proceedings of the 1996 // IEEE International Symposium on Intelligent Control. 1996. P.277 - 281.
- Joseph D.D. Fluid Dynamics of Viscoelastic Liquids. Spinger-Verlag. New York Inc. 1990. P.755.
- Bernstein B., Kearsley E.A., Zapas I.J. A Study of Stress Relaxation with Finite Strain // Trans. Soc. Rheol. 1963. V. 7. P. 397 - 410.
- Wagner M.H. A Constitutive Analysis of Uniaxial Elongation Flow Data of a Low Density Polyethilene Melt. // J. Non-Newtonian Fluid Mech. 1978. N. 4. P. 39 - 55.
- Yanovsky Yu.G., Basistov Yu.A. and Siginer D.A.Linear Inverse Problems in Viscoelastic Continua and a Minimax Method for Fredholm Equation of the First Kind // Int. J. Engng Sci. 1996. V.34. N.11. P. 1221 - 1245.
- Basistov Yu.A., Yanovsky Yu.G. Ill-Posed Problems under Identification of Non-Linear Rheological Models of State // Proceedings of the 6th European Conference on Rheology. Erlangen. 2002. September 1-6.
- Yanovsky Yu.G., Basistov Yu.A., Filipenkov P.A.Problem of Identification of Rheological Behavior of Heterogeneous Polymeric Media under Finite Deformation // Proceeding of the XIV International Congress on Rheology. TheKoreanSocietyofRheology. 2004. SO18-1 - SO18-3.
- Басистов Ю.А., Яновский Ю.Г. Нелинейные модели вязкоупругих сред и их идентификация. Механика композиционных материалов и конструкций. 2005. Т. 11. №2.С.306 - 320.
- Яновский Ю.Г., Басистов Ю.А. Линейная динамическая нейросетевая модель вязкоупругой среды и ее идентификация // Механика композиционных материалов и конструкций. 2005. Т. 11. № 4. С. 589 - 615.
- Cohen M.A., Grossberg S. Absolute Stability of Global Pattern Formation and Parallel Memory Storage by Competitive Neural Networks // IEEE Transaction on System. Man and Cybernetics. 1983. V.SMC-13. P.815 - 826.
- ХайкинС.Нейронныесети. Москва-С.Петербург-Киев: «Вильямс». 2006.
- Li J., Michel A.N., Porod W. Analysis and Synthesis of a Class of Neural Networks: Linear Systems Operating on a Closed Hypercube // IEEE Transactions on Circuits and Systems. 1989. V.36. N. 11. P.1405 - 1422.