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The paper is to propose a framework to qualitatively and quantitatively evaluate five of state-of-the-art over-segment approaches. Moreover upon over-segments evaluation, an efficient approach is developed for dense stereo matching through robust higher-order MRFs and graph cut based optimization, which combines the conventional data and smoothness terms with the robust higher-order potential term...
In this paper, we propose a robust transceiver design for the K-pair quasi-static MIMO interference channel. Each transmitter is equipped with M antennas, each receiver is equipped with N antennas, and the kth transmitter sends Lk independent data streams to the desired receiver. In the literature, there exist a variety of theoretically promising transceiver designs for the interference channel such...
In this paper, we consider a robust approximate lattice alignment design for K-pairs quasi-static MIMO interference channels. The traditional interference alignment on the signal space is infeasible for K > 3 and perfect channel state information (CSI) is required for all the alignment schemes in the literature, which is impractical in practice. Furthermore, the structured lattice, widely used...
A novel Self-organizing Quantum Evolutionary Algorithm for Multi-objective optimization(MSQEA) is proposed. The technique for improving the performance of MSQEA has been described. By using self-organizing co-evolution strategy each subpopulation can obtain more optimal solutions. Because of the quantum dynamic mechanism all the subpopulations may move concurrently in a force-field until all of them...
To avoid premature convergence and stagnation problems in classical ant colony system, a novel multi-behavior based multi-colony ant algorithm (MBMCAA) is proposed. The ant colony is divided into several sub-colonies; the sub-colonies have their own population evolved independently and in parallel according to four different behavior options, and update their local pheromone and global pheromone level...
A novel parallel quantum evolutionary algorithm based on chaotic searching technique (PCQEA) is proposed. In the algorithm, the use of a chaotic searching technique provides this methodology with superior global search ability; several antibody diversification schemes were incorporated into the algorithm in order to enhance the exploitation and exploration. It can help to obtain the multi-modal optimal...
According to the high-order nonlinearity and parameter uncertainty of the ship steering dynamics, it is difficult to establish the accurate mathematical model by using normal identification methods. To solve this problem, a new kind of support vector regression based on the ant colony algorithm (ACA-SVR) is proposed. This method can select the parameters of SVR automatically without trial and error,...
Support vector machines (SVM) is a powerful supervised learning method. It has been used mostly for regression and classification. Some SVM parameters are usually selected artificially, which hampers the efficiency of the SVM algorithm in practical applications. A improved artificial fish swarm algorithm (IAFSA) based on the predatory search strategy of animals was used to optimize the parameters...
This paper presents a novel cultural algorithm, in which an adaptive Cauchy mutated particle swarm optimizer (ACMPSO) is used as a population space; the Cauchy allows larger mutations and in this way producing more diversified individuals and covering more major space. The knowledge sources contained in the belief space are specifically designed according to the ACMPSO evolution features. Different...
In this paper, a micro jet based cooling system for the thermal management of high power LEDs is briefly introduced. Our experiments have demonstrated that the optimization on micro jet device is strongly needed for improving the system performance. To realize the above attempt, numerical optimization on micro jet device is conducted in details in this paper. The comparison between simulation and...
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