Abstract:In order to overcome the defects of shuffled frog leaping algorithm (SFLA) such as slow searching speed in the late evolution and easily trapping into local extremum, an Improved Shuffled Frog Leaping Algorithm (ISFLA) based on the basic ideas of Molecular Dynamics (MD) simulations is put forward in this paper in which the population is regarded as molecular system. We propose a new intermolecular force instead of the classic two-body Lennard-Jones force and use Velocity-Verlet algorithm and Gaussian mutation instead of the original SFLA update strategy, which balance the population diversity and search efficiency effectively. The test results on high-dimensional and multi-modal optimization problems indicate that ISFLA improves the capacity of escaping from local maximum and the global searching performance is superior to SFLA.

Abstract:Clustering analysis is a classical approach to mine the useful information from huge maritime database. In order to do clustering for large amounts of samples, considering most adjustments of clusters happen in the initial stage of iteration in the clustering process of k-means algorithm, this paper proposes an accelerated clustering analysis algorithm based on cluster’s threshold-adjusted. Experiments proved that the improved algorithm can not only obtain good clustering result, but also accelerate the speed of clustering. Finally an application of clustering is given for designing routes from the marine database，which is very important for maritime intelligent transport system.

Abstract:The relation between the emotion dimension space and speech features is studied in this paper, and the automatic speech emotion recognition problem is addressed. Dimensional space model is introduced for basic emotions. Speech emotion features are extracted according to the arousal dimension and the valence dimension, statistic features are used to reduce the influence on emotional features due to the text variations. Anger, happiness, sadness and the neutral state is studied. Gaussian mixture model is adopted for modeling and recognizing the four emotion classes, the Gaussian mixture number is optimized in the experiment for good approximation of the probability distribution in the feature space. The experimental results show that, the features used in this paper are suitable for recognizing the basic emotions. The Gaussian mixture model achieves satisfactory classification results, and the importance of the valence features in the two dimensional space is presented in the recognition experiments.

Abstract:Abstract:The adjacent frame difference is a common approach used in motion detection of video surveillance, however, this method does not suit for the case of high speed dense video surveillance. Based on this case, we propose a new and simple technique to reconstructing background of high speed dense surveillance sequences in this paper. Our method is first to extract public background of video sequences, by using the property of space distribution of a frame difference sequence and the high order statistics theory, then to form a sequence of road background by removing the background interference caused by motion according to the distribution similarity of a background frame difference image and thereby to get a road background image, finally to refresh the background image via an adaptive method of the scoreboard. The experimental results demonstrate the effect of our scheme is apparent. That is to say our scheme is a new one for reconstructing background and detecting motion target in high speed video.

Abstract:To estimating the azimuth and elevation by long baselines, a method of direction finding based on module theory is presented. According to operation mode and condition for correct ambiguity resolution, the expressions for the probability of correctly resolving the ambiguity as a function of the phase errors are derived. Results of the Monte-Carlo experiments are given to confirm the correctness of the probability distribution function. Theoretical analysis and experiments show the method has high probability of correct ambiguity resolution and angular accuracy.

Abstract:Recognition of atherosclerotic plaque is premise of adopting treatment measures in clinic; Automatic recognition can overcome the effect of subjective factors. Characters of plaque are extracted by gray level co-occurrence matrix, and then SVM is applied to construct classifier combining PSO algorithm, which optimizes parameters of SVM based on Gaussian radius basis kernel function. The result shows that rate of recognition reaches 92%.The method improves accuracy, scientific and objectivity in diagnosing cardio-cerebrovascular disease in clinic.

Abstract:Process for the research of early fire segmentation technology, the article proposes a fuzzy clustering segmentation algorithm based on multi-dimensional color vector space. This algorithm uses the moving object image sequence variation region as a clustering template. When template is ready, its RGB eigenvectors are extracted and then the segmentation can be continued by using this clustering template. The arithmetic can be easily operated and time overhead. By this algorithm, a better picture of morphological characteristics of the flame edge can be obtained, the segmentation error under different light can significantly be eliminated, and fast unsupervised automatic segmentation can be completed.

Abstract:A method for age estimation of facial images is proposed based on the combination of the Gabor wavelets and the histogram sequence of the local binary pattern (LBP). First, the facial images are filtered by the multi-orientation and multi-scale Gabor before Gabor magnitude maps (GMMs) are extracted. Second, the local neighbor pattern on GMMs is extracted by LBP based on local characteristics, which is divided into several sub-blocks from which calculate the histogram sequences. Third, to further reduce the dimension of facial features, PCA is applied to the histogram sequences. Finally, a leave-one-person-out (LOPO) test scheme of the support vector regression (SVR) is used to train and test the face age database. Experimental results show that the method can quickly and effectively estimate the age of human faces.

Abstract:Monopulse angle estimation algorithm based on adaptive sidelobe canceller is analyzed in this paper. Because of the mismatch problem, interested signal can not be cancelled completely by blocking matrix, which results in the leakage of interested signal in auxiliary channel. Performance of monopulse angle estimation also degrades as a result. To solve this problem, an improved method is proposed. Orthogonality relationship between signal space and interference space is used in this method to reduce the effect of the leakage of interested signal in auxiliary channel. Theoretical and simulation results are given to prove the effectiveness and superiority of this method.

Abstract:The Bayer GWR algorithm is proposed to obtain the high-quality color image for embedded machine vision system. The method changes the original GWR input parameters according to the structure of Bayer CFA. Using tricolor’s each mean value to replace their sum value in the GW assumes of GWR, and the each mean value of the near white point to replace their maximum in the Retinex assumes of GWR. Test shows: the method can effectively reduce the color temperature with a low data computation and process the 640?480 original image data in the smart camera with 600MHz within 34 ms. It can satisfy the practical application of practical and real-time requirements.

Abstract:In elevator group control system, to choose the weight values of multi-objective optimization problem is always subjected to the designers’ understanding and personal preference, so sometimes the weight values can’t directly reflect the real change of elevator’s performance with the weight coefficients. If we put the Pareto solution set into the research of choosing the weight values, and use the random weight method, after one time, we can get several groups of different weight values, then seek the optimal Pareto solution according to the elevator dispatching strategies generated by different weight values. Because this algorithm can provide us several groups of different and optimal elevator dispatching strategies, at the same time, provide the researchers more useful data to refer. According to the advantages and disadvantages of each algorithm, we join gradient decent algorithm with the clonal selection algorithm, and speed up the convergence rate in later period, define random balanced traffic flow between layers as passengers flow, put hybrid algorithm and clonal selection algorithm into elevator group control system to find the saving energy policy, to some extent, hybrid algorithm has much more superiority than clonal selection algorithm.

Abstract:There are various objects on the earth, for which traditional classification methods can hardly considering their diversity and specific characteristics; therefore, it is difficult to obtain stable and precise classification results. Under this circumstance, an adaptive extraction method based on spectral matching, is proposed to extract thematic object completely and accurately from remote sensing image. This algorithm first selects the endmember of thematic object, and use spectral matching method to get the matching index; then, histogram threshold based auto-segmentation method is used to initially separate thematic object from background; next, thematic object pixels are searched out and taken as seed points to proceed region growing to gain the local area of thematic object; last, the boundary of the local area is searched and iterative classification within the local area is employed to precisely extract thematic object’s precise partition. Experiments on ETM image to extract water and bareland are employed here, and through comparison with maximum likelihood classification and support vector machine (SVM) classification, it verifies the effectiveness and commonality of this method.

Abstract:In the frequency estimation of multi-segment signals, the error caused by discontinuity among different segments cannot be ignored. By correcting the phase difference of each segment, the results can be enormously improved, but the computational complexity of the algorithm grows on the same time. To resolve this problem, a new fusion algorithm based on spectrum zooming is proposed. The new algorithm performs spectrum zoom analysis to reduce the computational complexity while the precision is guaranteed, which is suitable to those real-time applications. Performance of the algorithm is demonstrated and analyzed through computer simulations.

Abstract:Because of the limitation of sampling equipments and sampled signal, it is hard to sample uniformly, and nonuniform sampling is widely used actually. When data are not sampled uniformly, the sampling theorem no longer applies. It’s effective to analysis the spectrum of the nonuniformly sampled signals by the means of spectrum analysis based on least square technique. The reason for spectral noise and its influence factors are discussed detailedly. Because some weak signal are inundated with the spectral noise, the method of amplitude damping based on least square technique is used to suppress the strong signal and spectral noise effectively. The weak signal, of which the amplitude is one hundred million times smaller than the strong one, is detected successfully in the simulation experiment, and the parameters of the components of nonuniformly sampled signal can be estimated with high accuracy.

Abstract:As existing adaptive algorithms need training bits and are unsuited to fast fading channel in WCDMA systems, a novel adaptive multiuser algorithm based on differential MMSE (DMMSE) criterion is presented in this paper. According to the typical characteristic of two-layered spreading modulation in the WCDMA systems, the proposed DMMSE criterion updates the weight coeffients of transversal filter by tracking the ratio of successive symbols with the same comprehansive spread sequence. Thanks to depict the multiple access interference (MAI) more properly, the proposed algritnm can suppress the MAI more effectively. Simulation results illustrate that proposed one performs better than the existed ones at the Doppler shift channel.

Abstract:In R9 version of LTE system, multi-user dual stream beamforming is proposed. To suppress inter-user interference of multi-user multiple input multiple output (MU-MIMO) systems, a new algorithm is presented in this paper. On condition that current user eliminates the interference to other users, it designs its own transmit beamforming vector; If all users take such measures, the interference each user suffers from others will be reduced to a minimum, which improves performance of the system.Compared with the traditional signal-to-leakage-and-noise ratio (SLNR) algorithm, simulation shows, as the number of user increases, the algorithm used in this paper can reduce the bit error rate (BER) of the system obviously.

Abstract:The reconstruction of plused magnetic flux leakage (PMFL) defects profiles is key for the quantitative study of defects characteristic. The used SVM kernel function can not approach to any object function in defects reconstruction. Aiming at this problem, based on the idea of multi-resolution approximation, the wavelet and the SVM are combine to form WSVM. Then，this method is introduced in 3-D defect reconstruction research in this paper. In the experiments, the horizontal component of magnetic flux density Bx is chosen as input data of WSVM nets, the defect geometric parameters: length, width and depth are output data. A mapping from PMFL response signals to 3-D profiles of defects was established, and the inversion of 3-D profiles of defects from magnetic flux leakage inspection signals was achieved. Experimental results show that the proposed method can combine the advantages of SVM and wavelet so that it obtains high precision and a good generalization ability, and capability of tolerating noise. It is a feasible method.

Abstract:Proposed a digital quadrature architecture without delay calibration filter and analyzed it’s performance, analyzed the frequency offset’s impact on the phase and phase difference. The simulation results shows that high Image Rejection Ratio (IRR) can be acquired when the frequency offset is little; otherwise, the phase difference error can be reduced by accumulating the multi-point phase differences. The proposed architecture has some advancements as simple, faster processing speed and easy to hardware realization, which could be widely applied, such as radar, electronic reconnaissance and so on. Applying this structure to the design of multi-channel digital receiver may decrease the occupation of the hardware resource to some extent, at the same time, satisfy the real time processing of the signal.

Abstract:Based on the principle of hormone modulation in endocrine system, an improved adaptive genetic algorithm was proposed. This algorithm designed an adaptive crossover operator and an adaptive mutation operator based on the downward form of Hill function, to make the crossover rate and mutation rate self-regulate according to the diversity of the population in each generation, and maintain the diversity at a reasonable level in the whole process of evolution. Experimental results of 4 test functions and 3D brain image segmentation showed the improved genetic algorithm can not only effectively maintain the diversity of the population, but also avoid premature, and performances of this algorithm are better than those of the other two adaptive genetic algorithms and traditional genetic algorithm.

Abstract:Based on the phase linearity of a pulse train, a coherency identification algorism is proposed to deal with pulse signals. The algorism is able to improve the signal-to-noise ratio (SNR) of the signal through coherent accumulation. The relationship between the threshold and the performance of the algorism is discussed in the paper. A formula of minimum SNR needed is presented. Simulation results show high performance of the proposed algorithm. The proposed algorism can be applied to the identification of the pulse Doppler radar. It also can help the development of the digital radio frequency memory (DRFM).

Abstract:A new algorithm for multi-angle estimation in bistatic MIMO radar based on the uniform circular array is presented in this topic. The output signal of the array antennas is analyzed, showing trilinear model characteristics. The multi-angle can be estimated from the matrices via low-rank decomposition based on the uniqueness of PARAFAC decomposition. The method doesn’t require searching spectral peak or pairing parameters .Compared with ESPRIT method，the proposed algorithm has high precision in parameter estimation and works well under small sizes. The simulation results verify its effectiveness.

Abstract:A new fast acquisition algorithm for two-dimensional direct sequence spread spectrum (2DSSS) signal which is realized on non-coding PSK modulation (PSK-2DSSS) is proposed in this paper. It can greatly reduce the redundant operations in conventional time domain correlation methods. Firstly, the received signal is compressed according to half-chip boundaries, under the control of NCO principles. Then, considering the periodic characteristic of the PRN code in the 2D spread spectrum sequence, the traditional acquisition flow is adjusted to eliminate the reduplicate multiply operations in correlation processing. As a result, the acquisition computational complexity is decreased significantly, at a cost of very slight performance degradation. Simulations confirm the correctness and effectiveness of the proposed method.

Abstract:Detecting near-duplicate images efficiently and accurately is very important for copyright infringement detection and redundancy removal in retrieval results. In order to solve the low efficiency of the traditional methods, a new near-duplicate image detection method based on E2LSH is proposed. Firstly, E2LSH is used to filter most of the non near-duplicate image pairs. Then, a pool of vastly reduced image pairs is further invested by BoVW for removing the wrong matches, thus realizing the near-duplicate image detection. Experimental results show that the novel method significantly speed up the detection without apparent degradation in performance and achieve a good balance between performance and efficiency.