Multiple-Input Multiple-Output- Orthogonal Frequency Division Multiplexing(MIMO-OFDM) is adopted to vehicular networks to increase the capacity,reliability and *** this paper,iterative demodulation and decoding algori...
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Multiple-Input Multiple-Output- Orthogonal Frequency Division Multiplexing(MIMO-OFDM) is adopted to vehicular networks to increase the capacity,reliability and *** this paper,iterative demodulation and decoding algorithms are studied to approach the capacity of MIMOOFDM vehicular *** analysing the drawbacks of the Gaussian approximation on the interference cancellation,NonGaussian approximation is proposed to enhance the performance of interference cancellation based detectors with large *** results demonstrate that the proposed non-Gaussian algorithm can achieve a significant performance gain over existing ones with high order constellations.
UAV can work in places that are dangerous, or not easy to reach for humans. However, due to active control and operating difficulties, it is still a challenge to develop fully autonomous flight in complex environments...
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ISBN:
(纸本)9781479914821
UAV can work in places that are dangerous, or not easy to reach for humans. However, due to active control and operating difficulties, it is still a challenge to develop fully autonomous flight in complex environments. This paper applies a novel heuristic dynamic programming for the UAV heading optimal tracking controller design, using kernel-based heuristic dynamic programming (KHDP). Kernel-based HDP is developed by integrating kernel methods and approximately linear dependence (ALD) analysis with the critic learning of HDP algorithm. Compared with conventional HDP where neural networks are widely used and their features were manually designed, the proposed algorithm can obtain better generalization capability and learning efficiency through applying the sparse kernel machine into the critic learning process of HDP algorithm. Simulation and experimental results of UAV heading optimal tracking control problems demonstrate the effectiveness of the proposed kernel-based HDP algorithm.
The behavior patterns and strategies of Internet Water Army in online forums are investigated in this paper. Internet Water Army focuses on the controlling and steering of cyber collective opinions, and adjusts their ...
The behavior patterns and strategies of Internet Water Army in online forums are investigated in this paper. Internet Water Army focuses on the controlling and steering of cyber collective opinions, and adjusts their behavior according to two principles: to avoid being exposed and to increase the ability to exert influence. To study how the ability of Internet Water Army to exert influence, we construct a multi-agent system with coevolution of topics and cyber collective behaviors and design the behavior patterns and strategies of Internet Water Army. Based on synthetic data and real data, we find that Internet Water Army dynamically adjusts their behavior strategy to maximize their influence and the effectiveness of strategy of Internet Water Army is closely related to the features of the users. Our work sheds insight on the design of viral marketing mechanism in e-commerce systems as well as on guiding collective behaviors in social media.
A bi-branchiate robot is presented for the inspection of the high-voltage power transmission lines. With a symmetrical mechanical structure, the robot can roll along the power lines and negotiating all the obstacles i...
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In this paper, the adaptive dynamic programming (ADP) approach is employed for designing an optimal controller of unknown discrete-time nonlinear systems with control constraints. A neural network is constructed for i...
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The boom of Flickr, a photo-sharing social tagging system, leads to a dramatical increasing of online social interactions. For example, it offers millions of groups for users to join in order to share photos and keep ...
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This paper develops an adaptive optimal control for the infinite-horizon cost of unknown nonaffine nonlinear continuous-time systems with control constraints. A recurrent neural network (NN) is constructed to identify...
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In this paper, a new self-learning method using policy iterative adaptive dynamic programming (ADP) is developed to obtain the optimal control scheme of discrete-time nonlinear systems. The iterative ADP algorithm per...
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In this paper, an H ∞ optimal tracking control scheme based on generalized Hamilton-Jacobi-Isaacs (GHJI) equation is developed for discrete-time (DT) affine nonlinear systems. First, via system transformation, the op...
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In this paper, we aim to solve an infinite-time optimal tracking control problem for a class of discrete-time nonlinear systems using iterative adaptive dynamic programming (ADP) algorithm. When the iterative tracking...
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