Applied Mechanics and Materials Vols. 380-384

Abstract: In multiuser MIMO uplink communications, it is necessary to design linear schemes that are able to suppress co-channel interferences (CCIs). In this paper, we propose a linear block QR decomposition (BQRD) which transforms the multiuser channel to a block upper triangular structure based on Gram-Schmidt orthonormalization and can obtain more diversity gain than traditional BD. And a optimal ordering criterion is proposed at last to do full study of BQRD scheme. Simulation results show that the BQRD with the optimal ordering proposed achieves much better performance than the non-ordering one.

Abstract: In intelligent vehicle detection, vehicle detection at night especially detection in the condition of urban street always remains a problem. This paper proposes an effective vehicle detection algorithm. Firstly it extracts effective vehicle edge by the method of embossment which eliminates light interference. Then we detect the vehicle moving area by frame difference method and calculate the threshold by OTSU algorithm. Finally the noise points are removed by erosion and expansion. This method can better extract the moving objects.

Abstract: This paper puts forward a gestures trajectory recognition method based on DTW. Through the direction characteristic to calculate trajectory characteristics, and through the coding to quantize direction characteristic, and at the same time, considering the direction of the cyclical, proposed a new distance equation for calculating distance. The experimental results prove that the method realized the dynamic gesture recognition in the complex static background.

Abstract: In order to solve the issue of high precision detection for mobile phone, an effective approach for triggering the GSM signal is proposed to make the phone transmit the frequency hopping signal which can be established without user interaction. An algorithm of time delay estimation for frequency hopping is proposed and verified by the simulation. The results show that bandwidth signal of frequency hopping can be used which leads to the estimation errors range of approximately [-4.3m, +4.3 and the multipath resolution is improved as well. The technique is therefore ideally suited for high precision of mobile station location.

Abstract: Using motion state of the equipment transducer to determine the presence of a weak signal is a common method of signal detection, whose core is to determine the system's phase change. There a many traditional ways to judge phase transition, but most of which have computational complexity and need a large amount of data which make them difficult to apply engineering practices. In order to solve these problems, this paper presents a detection method based on Lyapunov exponent classification with a small amount of data. This approach has some advantages such as requiring fewer observed values, small calculation amount, and able to automatically determine the phase transition without subjective factors involved etc. Experiments show that this method has stable performance, high effectiveness, strong practicality and promotion.

Abstract: An advanced method is proposed that combines the advantage of Hough transform and exemplar method for human detection. This method firstly uses a universal codebook for all the patches in an image which reduces the total codebook size and the dimensionality of similarity features. Another contribution is in classifying and detection, in which section we use the sprite of Hough transform, but we train the model in a boost way. Finally the experiment results are given.

Abstract: Recent years, the common adaptive edge detection algorithms use merely the global character of images, and the local character is ignored. The lack of image information always leads these algorithms are difficult to detect the low contrast edges and sensitive to asymmetric illumination. A novel adaptive edge detection algorithm is proposed to improve the edge detection performance. First, the original image is filtered to obtain the edge response image by introducing multi-scale Gabor filters. Second, non-maxima suppression technique is used on the edge response image to get the coarse edge points. Then, the edge response image is delaminated to adaptively select different thresholds towards different pixels of different layers according to pixels local mean and variance values. The fine edge points are got after filtering the edge response image with these thresholds. Finally, combine the coarse edge points and fine edge points together and get the final edge. Experimental results show that the proposed algorithm achieves lower contrast edge detection and robustness to asymmetric illumination, has better edge detection performance.

Abstract: in order to solve the adverse effects of strong light and shadow on the test results, a fusion frame difference and background subtraction method in the HSV space is used in this paper. By using frame difference method to solve the effect of strong light, but frame difference method can not detect object when the object do not move, the method of background subtraction can detect it, building Gaussian background model in the HSV space can eliminate shadows. Empirical results show that the method of fusion frame difference and background subtraction in the HSV space can get overcome the effect of strong light and shadows. Fusion background subtraction and frame difference method based on establishing a Gaussian mixture model in HSV space can overcome the disadvantages of the frame difference method, at the same time it can also solve the false detection of object which result from the background subtraction method.

Abstract: For the vast amounts of heterogeneous data is difficult to effectively deal with the problem, propose an ontology-based data integration technology. Analysis of the types of semantic conflicts in data integration, ontology semantic description of traditional data integration framework for data integration middleware module. Ontology concept in the domain of information resources, and take the initiative to find and build semantic mapping between semantic conflicts.

Abstract: A novel framework of sub-Nyquist sampling and reconstruction for linear frequency modulation (LFM) radar echo signal based on the theory of blind compressive sensing is proposed. This mechanism takes LFM echo signals as a sparse linear combination under an unknown order p of fractional Fourier transform (FRFT) domain. Firstly, make use of good energy concentration of LFM signal in proper FRFT domain to determine the optimal order, which meets the convergence conditions. Secondly, construct DFRFT basis dictionary according to the specific sparse FRFT domain dominated by p. To reconstruct the sources, the simple orthogonal matching pursuit (OMP) is chosen with less data storage and lower computational complexity. Finally, simulations are taken on testing the proposed framework, realizing the undersampling and reconstruction without the knowledge of priori sparse basis for LFM radar echo signals, and the results are provided to verify the feasibility and efficiency of the novel method.