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Optimal excitation signal design for frequency domain system identification using semidefinite programming
The optimal excitation signal and the dispersion function semidefinite programming linear matrix inequality (lmi)
2015/8/11
The paper discusses two methods of optimal excitation signal design for identification with Maximum Likelihood parameter estimation: The ‘classical’, dispersion function based method, and a new, semid...
Semidefinite programming
Semidefinite programming linear function affine combination symmetric positive semidefinite matrix nonlinear not smooth
2015/8/11
In semidefinite programming we minimize a linear function subject to the constraint that an affine combination of symmetric matrices is positive semidefinite. Such a constraint is nonlinear and nonsmo...
Applications of second-order cone programming
Second-order cone programming linear function affine sets linear nonlinear convex problem quadratic program
2015/8/11
In a second-order cone program (SOCP) a linear function is minimized over the intersection of an affine set and the product of second-order (quadratic) cones. SOCPs are nonlinear convex problems that ...
Min-max approximate dynamic programming
Dynamic planning policy dynamic system the noise the approximation function
2015/8/7
In this paper we describe an approximate dynamic programming policy for a discrete-time dynamical system perturbed by noise. The approximate value function is the pointwise supremum of a family of low...
Approximate dynamic programming via iterated Bellman inequalities
Convex Optimization Dynamic Programming Stochastic Control
2015/8/7
In this paper we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based ...
Extensions of Gauss quadrature via linear programming
Gauss quadrature Semi-infi nite programming Convex optimization
2015/8/7
Gauss quadrature is a well known method for estimating the integral of a continuous function with respect to a given measure as a weighted sum of the function evaluated at a set of node points. Gauss ...
Quadratic approximate dynamic programming for input-affine systems
approximate dynamic programming stochastic control convex optimization
2015/8/7
We consider the use of quadratic approximate value functions for stochastic control problems with input-affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic progra...
A semidefinite programming method for integer convex quadratic minimization
The quadratic function the probability of integer zinc, values
2015/8/7
We consider the NP-hard problem of minimizing a convex quadratic function over the integer lattice Zn. We present a semidefinite programming (SDP) method for obtaining a nontrivial lower bound on the ...
Optimising a nonlinear utility function in multi-objective integer programming
nonlinear utility function multi-objective integer programming
2010/11/15
In this paper we develop an algorithm to optimise a nonlinear utility function of multiple objectives over the integer nondominated set. Our approach is based on identifying and updating bounds on th...
Relationship Between Dynamic Programming and the Maximum Principle under State Constraints
Dynamic Programming Maximum Principle State Constraints
2009/1/22
Bellman's dynamic programming and Pontryagin's maximum principle are two basic tools for studying optimal control theory. We consider the optimal control problem under state constraints and examine th...
Absolute Minimizer in Convex Programming by Exponential Penalty
Convexity minimax problems penalty methods nonuniqueness optimal trajectory convergence
2009/1/13
We consider a nonlinear convex program. Under some general hypotheses, we prove that approximate solutions obtained by exponential penalty converge toward a particular solution of the original convex ...