Results 31 to 40 of about 285,904 (328)
IEEE Access, 2022 In this study, we propose a method to balance between user fairness and energy efficiency of users in the context of simultaneous wireless information and power transfer (SWIPT)-based device-to-device (D2D) networks.
Eun-Jeong Han, Muy Sengly, Jung-Ryun Lee
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Fourth Order Gradient Symplectic Integrator Methods for Solving the Time-Dependent Schr\"odinger Equation [PDF]
, 2000 We show that the method of splitting the operator ${\rm e}^{\epsilon(T+V)}$ to fourth order with purely positive coefficients produces excellent algorithms for solving the time-dependent Schr\"odinger equation.
Chen, C. -R., Chin, Siu A.
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Adaptive vector greedy splitting algorithm [PDF]
, 2021 We introduce a new transform through a construction that we have called the Adaptive Vector Greedy Splitting algorithm. The main idea behind this algorithm is an optimization step based on the simple Bathtub Principle. We use the Vector Greedy Splitting algorithm to build orthonormal bases for a given vector of random variables (also called signals). A
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Convergence of Two Splitting Projection Algorithms in Hilbert Spaces
Mathematics, 2019 The aim of this present paper is to study zero points of the sum of two maximally monotone mappings and fixed points of a non-expansive mapping. Two splitting projection algorithms are introduced and investigated for treating the zero and fixed point ...
Marwan A. Kutbi +2 more
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Split algorithms for multiobjective integer programming problems
Computers & Operations Research, 2022 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Özlem Karsu, Firdevs Ulus
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Fixed Point Theory and Algorithms for Sciences and Engineering, 2021 Splitting algorithms for finding a zero of sum of operators often involve multiple steps which are referred to as forward or backward steps. Forward steps are the explicit use of the operators and backward steps involve the operators implicitly via their
Minh N. Dao, Hung M. Phan
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Fast Multiple-Splitting Algorithms for Convex Optimization [PDF]
SIAM Journal on Optimization, 2012 We present in this paper two different classes of general $K$-splitting algorithms for solving finite-dimensional convex optimization problems. Under the assumption that the function being minimized has a Lipschitz continuous gradient, we prove that the number of iterations needed by the first class of algorithms to obtain an $ $-optimal solution is ...
Goldfarb, Donald, Ma, Shiqian
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Variable Metric Forward-Backward Splitting with Applications to Monotone Inclusions in Duality
, 2012 We propose a variable metric forward-backward splitting algorithm and prove its convergence in real Hilbert spaces. We then use this framework to derive primal-dual splitting algorithms for solving various classes of monotone inclusions in duality.
Combettes, Patrick L., Vũ, Bang C.
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A new Approach for the Modulus-Based Matrix Splitting Algorithms
IEEE Access, 2019 We investigate the modulus-based matrix splitting iteration algorithms for solving the linear complementarity problems (LCPs) and propose a new model to solve it.
Wenpeng Wang +3 more
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Convergence rate analysis of primal-dual splitting schemes
, 2015 Primal-dual splitting schemes are a class of powerful algorithms that solve complicated monotone inclusions and convex optimization problems that are built from many simpler pieces.
Davis, Damek
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