An efficient co-evolutionary multi-objective particle swarm optimizer named ECMPSO was *** uses dynamic multiple swarms to deal with multiple objectives,taking one objective is optimized by each swarm into account,and...
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An efficient co-evolutionary multi-objective particle swarm optimizer named ECMPSO was *** uses dynamic multiple swarms to deal with multiple objectives,taking one objective is optimized by each swarm into account,and maintains diversity of new found non-dominated solutions via adopts a three-level particle swarm optimization(PSO) updating rule wherein the particles learn their experiences based on personal,neighborhood,and external *** prove the validity of the ECMPSO algorithm for solving multi-objective problems,some benchmark problems and one real-life problem are selected to validate the performance of the ECMPSO *** experiment results show that the ECMPSO algorithm is better in terms of search precision and convergence performance than other three algorithms from the literature.
Coordinated multi-point (CoMP) has been raised to increase the average cell throughput and the cell-edge user throughput. However, the energy consumption of mobile stations (MSs) is a key problem restricting the wide ...
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Adaptive filters such as the normalized least mean square algorithm are popularly used to deal with acoustic feedback problem in hearing aids. This algorithm has to compromise between fast convergence and low misalign...
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According to the compressed sensing (CS) theory, we can sample a sparse signal at a rate that is (much) lower than the required Nyquist rate, while still enabling a nearly exact reconstruction. imagesignals are spars...
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Optic Disk (OD) detection plays an important role for fundus image analysis. In this paper, we propose an algorithm for detecting OD mainly based on a classifier model trained by structured learning. Then we use the m...
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ISBN:
(纸本)9781467396769
Optic Disk (OD) detection plays an important role for fundus image analysis. In this paper, we propose an algorithm for detecting OD mainly based on a classifier model trained by structured learning. Then we use the model to achieve the edge map of OD. Thresholding is performed on the edge map to obtain a binary image. Finally, circle Hough transform is carried out to approximate the boundary of OD by a circle. The proposed algorithm has been evaluated on the public database and obtained promising results. The results (an area overlap and Dices coefficients of 0.8636 and 0.9196, respectively, an accuracy of 0.9770, and a true positive and false positive fraction of 0.9212 and 0.0106) show that the proposed method is a robust tool for the segmentation of OD and is very competitive with the stage-of-the-art methods.
Video steganalysis takes effect when videos corrupted by the target steganography method are available. Nevertheless, classical classifiers deteriorate in the opposite case. This paper presents a method to cope with t...
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We present a scheme for the practical decoy-state quantum key distribution with heralded single-photon source. In this scheme, only two-intensity decoy states are employed. However, its performance can approach the as...
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We present a scheme for the practical decoy-state quantum key distribution with heralded single-photon source. In this scheme, only two-intensity decoy states are employed. However, its performance can approach the asymptotic case of using infinite decoy states. We compare it with the standard three-intensity decoy-state method, and through numerical simulations, we demonstrate its significant improvement over the three-intensity method in both the final key rate and the secure transmission distance. Furthermore, when taking statistical fluctuations into account, a very high key generation rate can still be obtained even at a long transmission distance.
In this paper, a wavelet sparse representation based beamforming is proposed to improve the resolution and contrast of plane wave emission ultrasound imaging. First, the received signals are described as the convoluti...
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In this paper, a wavelet sparse representation based beamforming is proposed to improve the resolution and contrast of plane wave emission ultrasound imaging. First, the received signals are described as the convolution of the target scatterers with the point spread function of the system. And then, the wavelet sparse representation model is deduced according to the fact that the target scatterers can be sparse represented in wavelet domain. The proposed algorithm was tested with simulated ultrasound data in plane wave emission. And the results demonstrated that the resolution was clearly improved and contrast ratio gains of 9.8 dB, 4.3 dB and 3.7 dB were obtained compared to delay-and-sum beamformer, minimum variance beamformer and phase coherence factor, respectively.
This paper investigates the secrecy capacity of a multi-antenna amplify-and-forward (AF) hybrid satellite-terrestrial relay netwrok (HSTRN), which consists of a satellite, a relay, a terrestrial destination and a terr...
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ISBN:
(纸本)9781467376884
This paper investigates the secrecy capacity of a multi-antenna amplify-and-forward (AF) hybrid satellite-terrestrial relay netwrok (HSTRN), which consists of a satellite, a relay, a terrestrial destination and a terrestrial eavesdropper. Specifically, by employing a two-stage beamforming (BF) scheme, where the relay first adopts the maximal ratio combining (MRC) to receive the signal from satellite and then performs zero-forcing (ZF) to completely null the eavesdropper's signal, the achievable secrecy capacity of the considered hybrid network is derived in closed-from. Eventually, simulation results are provided to demonstrate the superiority of the proposed BF scheme as well as the validity of the theoretical results, and show the effect of various channel parameters on the system performance.
Noise contamination is inevitable in biomedical recordings. In some cases biomedical recordings are highly contaminated with artifacts which make the effective recovering process hard to achieve. Many different method...
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ISBN:
(纸本)9781479984992
Noise contamination is inevitable in biomedical recordings. In some cases biomedical recordings are highly contaminated with artifacts which make the effective recovering process hard to achieve. Many different methods have been proposed for artifact removal from biomedical signals but introducing an effective method which can present valuable data for medical analysis, is still an ongoing process. In this paper a new method for interictal EEG denoising is presented. Single-channel ICA denoising method based on EMD decomposition is used to improve the multi-channel ICA denoising results. This method is tested on simulated epileptic recordings which are contaminated with real muscle artifact and EEG background activity.
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