Results 271 to 280 of about 9,520,135 (306)
Movable Antenna-Enabled RIS-Assisted Simultaneous Wireless Information and Power Transfer Systems. [PDF]
Sensors (Basel)Feng D, Zhang X, Yu X, Wang X, Shi X.
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Modified prioritized DDPG algorithm for joint beamforming and RIS phase optimization in MISO downlink systems. [PDF]
Sci RepShukry S, Fahmy Y.
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Dynamic Dual-Antenna Time-Slot Allocation Protocol for UAV-Aided Relaying System Under Probabilistic LoS-Channel. [PDF]
Sensors (Basel)Huang P +5 more
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Environment-Dependent Downlink Pinching-Antenna Systems: Spectral-Energy Efficiency Tradeoffs and Design. [PDF]
Sensors (Basel)Zha X, Chen Y, Wang Q.
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Stochastic Successive Convex Approximation for Non-Convex Constrained Stochastic Optimization
IEEE Transactions on Signal Processing, 2019 This paper proposes a constrained stochastic successive convex approximation (CSSCA) algorithm to find a stationary point for a general non-convex stochastic optimization problem, whose objective and constraint functions are non-convex and involve ...
Lau Vincent K N, Liu An
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2001
In the previous chapter, we study the minimization problem of a convex function under convex constraints. In this chapter, we study the minimization problem for two other classes of functions. The first ones are quasi-convex functions. We know (see Chapter 5) that for a convex function f, any level set of f is convex. But the converse is not true.
Monique Florenzano, Cuong Le Van
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In the previous chapter, we study the minimization problem of a convex function under convex constraints. In this chapter, we study the minimization problem for two other classes of functions. The first ones are quasi-convex functions. We know (see Chapter 5) that for a convex function f, any level set of f is convex. But the converse is not true.
Monique Florenzano, Cuong Le Van
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Pareto Optimality in Non-Convex Economies
Econometrica, 1975This article uses the concept of "cone of interior displacements," which extends the notion of differentiability, to set up a characterization of Pareto optima in non-convex economies. A general theorem asserting that a Pareto optimum is a PA equilibrium is given and specifications are discussed.
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SPIE Proceedings, 1986
A stochastic search technique called simulated annealing can solve a class of problems termed non-convex optimization by seeking the lowest minimum of a multi-minima function. Simulated annealing is a generalized Monte Carlo technique with a continuously decreasing variance controlled by the temperature parameter.
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A stochastic search technique called simulated annealing can solve a class of problems termed non-convex optimization by seeking the lowest minimum of a multi-minima function. Simulated annealing is a generalized Monte Carlo technique with a continuously decreasing variance controlled by the temperature parameter.
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Non-Convex Optimization: A Review
2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), 2020With the rapid development in technology, Artificial Intelligence is responsible for giving solution to every new problem in technology. Artificial Intelligence is the combat process of application, implementation and self- correction. The most potential application of Artificial Intelligence is Machine Learning.
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A Non-convex Optimization Model for Signal Recovery
Neural Processing Letters, 2020The electroencephalogram (EEG) signal is one of the most frequently used biomedical signals. In order to accurately exploit the cosparsity and low-rank property which is nature in multichannel EEG signals, motivated by the fact that weighted schatten-p norm and $${l_q}$$ norm can better approximate the matrix rank and $${l_0}$$ norm, in this paper, a ...
Changwei Chen, Xiaofeng Zhou
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