Convex Programming
APPLICATION TO CONVEX PROGRAMMING
... for convex sets, let us now consider a class of convex programming problems, where we seek to minimize convex functional subject to convex ...
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Stability in E convex programming
... Abstract. We define and analyze two kinds of stability in E-convex programming problem in which the feasible domain is affected by an operator E. The first kind of this stability is that the set of all ...
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Convex programming for detection in structured communication problems
... tively (Boyd and Vandenberghe, 2004). Generalized mini- mum mean squared error detector is one important detector that uses convex programming to solve the detection prob- lem using unconstrained gradient ...
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Some Multi Convex Programming Problems Arising in Multivariate Sampling
... The problems of multivariate sampling arising in the areas of stratified random sampling, two stage sampling, double sampling and response errors formulate as multiobjective convex programming problems with ...
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Optimality conditions of E convex programming for an E differentiable function
... 2. Youness, EA: Optimality criteria in E-convex programming. Chaos Solitons Fractals 12, 1737-1745 (2001) 3. Chen, X: Some properties of semi-E-convex functions. J. Math. Anal. Appl. 275, 251-262 ...
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Optimality and mixed duality in multiobjective E convex programming
... This paper also addresses a counterexample of Theorem . in Youness []. Character- ization of efficient solutions based on the modification of Theorem . in Youness [] is presented. A sufficient optimality theorem is ...
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Convex Programming Based Phase Retrieval: Theory and Applications
... side, convex programming based approaches have played a key role in modern phase retrieval, inspired by their success in provably solving several quadratic constrained ...
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Multi-class Discriminant Kernel Learning via Convex Programming
... solving convex programs in the case of support vector machines (SVM) (Vapnik, 1998; Cristianini and Taylor, ...prescribed convex set of kernels by ...
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Simultaneous Phase Retrieval and Blind Deconvolution via Convex Programming
... novel convex formulation that is possible because the algebraic structure from lifting resolves the bilinear ambiguity just enough to permit a non-trivial convex relaxation of the ...novel convex ...
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On the Stable Sequential Kuhn Tucker Theorem and Its Applications
... The second important feature of the classical Kuhn- Tucker theorem is its instability with respect to per- turbations of the initial data. This instability occurs even for the simplest finite-dimensional convex ...
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Chebyshev Approximate Solution to Allocation Problem in Multiple Objective Surveys with Random Costs
... a convex programming problem with non-linear objective functions and a single stochastic cost ...constrained programming. The resulting multi- objective convex programming problem is ...
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Optimality Conditions and Duality for DC Programming in Locally Convex Spaces
... locally convex Hausdorff topological vector spaces, whose respective dual spaces, X ∗ and Y ∗ , are endowed with the weak ∗ -topologies w ∗ X ∗ , X and w ∗ Y ∗ , Y ...proper convex functions, and let A : X → ...
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Some Properties of Generalized Strongly Harmonic Convex Functions
... mathematical programming, have been extended using innovative ideas and ...harmonic convex functions on the harmonic convex set can be characterized by a class of variational inequalities, which is ...
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A Simple Strategy to Tackle Mutual Coupling and Platform Effects in Surveillance Systems
... on convex programming ...a convex programming ...a convex synthesis procedure, that guarantees to reach the global optimum in a very short ...
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Mask-Constrained Power Synthesis of Large and Arbitrary Arraysas a Few-Samples Global Optimization
... In the case of fixed-geometry arrays (wherein the antenna layout is a-priori assigned while the elements’ excitations are the only unknowns), the problem has been solved in a globally-optimal fashion in both cases of ...
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Optimality for \(E\mbox{ }[0,1]\) convex multi objective programming problems
... multi-objective programming problems was very active in recent ...generalized convex functions. The definition of generalized convex functions has occu- pied the attention of a number of ...
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1112.1436.pdf
... and to Waksman and Epelman [47] for another related result. For perturbation results we refer to Borwein and Moors [13, 14]; the latter paper shows that the set of linear maps under which the image of a closed ...
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A simple randomised algorithm for convex optimisation: Application to two-stage stochastic programming
... Two main directions have been taken in the literature to arrive at sensible models. In the con- ceptually easiest, violation of the uncertain constraints is allowed to occur with a probability that does not exceed a ...
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PERFORMANCE ANALYSIS AND IMPROVEMENT STRATEGY FOR CONVEX ENVELOPE GENERATION ALGORITHM FOR PARALLEL PROGRAMMING
... parallel programming models; Parallel programming models exist as an abstraction above hardware and memory ...parallel programming models using a pure shared or distributed memory approach, shared ...
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Fixed Point Iteration Method for Solving the Convex Quadratic Programming with Mixed Constraints
... We assumed that θ ( ) t is a convex and differentiable function, which indicate one can apply the classical Newton-type algorithm directly. And the assumption θ ′ ( ) 0 > 0 means that 0 is not a sub-gradient of ...
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