Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problem of imaginary part interference in channel estimation of FBMC system, this paper proposed a new channel estimation algorithm. Firstly, the algorithm adopted a new pilot structure based on imaginary part interference cancellation. Then, two columns of pilots are used for rough channel estimation respectively. Finally, the weighted channel estimation is used for the coarse channel estimation, which further improved the channel estimation performance. Simulation results show that the new pilot structure algorithm can achieve the performance improvement of 1dB-2dB when the bit error rate is 1% compared with the traditional imaginary part interference cancellation algorithm (IIE) .
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： To solve the disadvantages of the most photovoltaic (PV) models parameter identification algorithms at present, which have low accuracy and poor reliability, this paper proposed an improved symbiotic organisms search (SOS) algorithm for parameter identification of PV module models. First, to enhance the performance of original SOS, a novel improved SOS algorithm, named as ImSOS, was proposed. In ImSOS, a quasi-reflection-based learning (QRBL) scheme was employed in the population initialization step of original SOS. Moreover, the strategy of the modifications of benefit factors was used in the mutualism phase of SOS. A strategy of narrowing the search range of randomly generated coefficients was adopted in the commensalism phase of SOS. And then, the procedures and flowchart of employing the proposed ImSOS for solving the PV module models parameter identification problem based on experimental current versus voltage (I-V) data of a real PV module was detailed. Finally, the proposed ImSOS was demonstrated on the parameter identification of different PV module models of the Sharp ND-R250A5 PV module. Experimental results and comparisons with original SOS and the other seven novel intelligent optimization algorithms implied the effectiveness and superiority of the proposed ImSOS. Therefore, the proposed ImSOS becomes a new effective method to accurately and reliably identify PV module models parameters.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-06-19 Cooperative journals: 《计算机应用研究》
Abstract： The software defined network (SDN) realizes the flexible control of the network through the controller, so the placement of the controller is critical to the overall performance of the network. This paper proposed an improved improved binary particle swarm optimization (IBPSO) algorithm to solve the controller placement problem. IBPSO algorithm determines the current value of particles based on both the global optimal and the individual optimal, thus weakening the influence of particle current value on the next iteration, and accelerating the convergence, which leaded to a better final result. The simulation results show that compared with the BPSO algorithm, the controller placement scheme obtained by this algorithm can significantly reduce the number of controllers while realizing the load balancing of the controller.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-24 Cooperative journals: 《计算机应用研究》
Abstract： In order to detect saliency object accurately, this paper proposed an efficient framework for saliency detection based on scatter-shape guidance and optimization function. First, it proposed a discriminative similar metric by taking color, spatial and edge information into consideration. Based on similar metric together with background set obtained by removing the foreground noise in the image boundaries with scatter-guided, it constructed a background based saliency map. In order to improve the quality of detection, it introduced the shape completeness cue to generate the corresponding shape completeness saliency map by measuring the completeness of a region by the expectation of times for which it bounded the region by completely shape over the hierarchical space. Finally, it achieved the final saliency map by integrating the above both maps jointly into an optimization function. Quantitative experiments on four available datasets ASD, DUT-OMRON and ECSSD demonstrate that the proposed method outperforms other state-of-the-art approaches and detects the salient object which locates at random positions.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at improving the traditional shape searching which needs to search in the whole shape space each time. A new approach is proposed based on classified face shape searching. This approach begins with a shape space that contains diverse shapes, first we optimize the random forest classifiers by the feature selection method of correlation-based and train the random forest classifiers by training samples, then divides the shape into several sub-spaces by random forest classifiers, and search the sub-space that most similar to the current shape, then estimate the center of the sub-space and probability distribution. Finally, employs cascaded regression to realize face alignment. The approach demonstrates its obvious decreases in searching time and its good robustness in unconstrained environment on the 300-W database.
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