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SYSTEM MODELLING AND IDENTIFICATION
Some Statements and Ways of Solving Dynamic Optimization Problems
Nonstationary Processes for Mathematical Programming Problems
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adjoint algorithm application approximation assume assumptions calculated coefficients compact computation consider constant constraints continuous convergence convex convex function convex set coordination corresponding criterion defined denote derivatives determined differential equations differential games distributed parameter systems distribution dynamic element equilibrium estimate Euler splines evaluation example exists extremum finite formula func fuzzy given gradient Hilbert space identification inequality initial input integral interval iteration Lemma limit linear manifold mathematical programming matrix maximum principle measurable method minimax minimax problem minimization minimum mixed strategy Moscow motion multistage games nonlinear Nonlinear Programming Novosibirsk objective function observation obtained open-loop open-loop control operator optimal control output parameters player polynomial positive possible quadratic random relations respect Russian saddle point satisfy sequence solution solved stochastic structure sub-systems sufficient technique Theorem theory tion trajectory unique unit circle USSR vector zero