Advanced Materials Research Vols. 403-408

Abstract: This paper divides the packets flowing through the gateway devices into two categories, the first one is sent to the gateway device itself and the other one is that the packets need to be forwarded by the gateway device. The port-based fast forwarding module in gateway mode proposed in this paper is an extended forwarding mode on the base of the traditional Linux network stack, which optimizes the system’s packet forwarding process, gets rid of the bridge forwarding and routing module and reduces system resources occupancy. The experimental results show that the fast forwarding mechanism in gateway mode can improve the system performance, and the classification model of the packet can greatly enhance the system’s stability and security.

Abstract: In this paper, we propose a novel algorithm for coarse-to-fine foreground objects extraction. There are two general approaches for foreground objects extraction: background subtraction and image matting. Our new approach can not only improve detection accuracy compared with general background subtraction approaches, but also reduce computation burden compared with general image matting approaches. Firstly, we present a novel method called Motion-mask Gaussian Mixture Models (Motion-mask GMMs) to extract coarse foreground regions. This new approach can classify foreground and background pixels more accurately, especially when there are long-time stopping objects in the scene. Secondly, with the coarse foreground regions, we propose a novel approach to make foreground object extraction more accurate based on effective fusion of image registration and image matting. This new method overcomes the template drift problem during template updating and also reduces the expensive computational cost of image matting. Our proposed approach is tested with kinds of video sequences in indoor and outdoor environments. Experimental results demonstrate the accuracy and efficiency of our proposed approach for foreground object extraction.

Abstract: In signal processing, a frequently encountered problem is harmonic retrieval in additive colored noise, especially false peaks existence in harmonic signal peaks. The purpose of this paper is to develop an efficient approach to clear the false peaks based on cross-high-order spectral QR decomposition approach. Simulation results indicate that spectral density curve is smooth without false peaks existence. The methods have better in resolving power and performance than previous MUSIC approach. Thus, this approach is ideally suited for harmonic retrieval in additive colored noise and short data conditions, and is also accurate to estimation signal parameter in hybrid colored noises.

Abstract: Motivated by the development of Multiple-Input Multiple-Output (MIMO) communication, MIMO radar has drawn considerable attention. While, to design of MIMO radar detector, transmitting signal power and noise are usually assumed known in advance, but in practice we may need to estimate the transmitting signal power and noise first. In this paper, we introduce MIMO radar target performance analysis with unknown parameters. First transmitting signal energy is estimated by Maximum likelihood Estimation(MLE) when multipath satisfy special diversity condition and multipath has low rank. Then the detector in the Neyman-Pearson is developed and analyzed with estimated parameters. The simulation results show that the performance with unknown parameters is approximate to the detector with known parameters. The method proposed in this paper can be used to design the MIMO radar detectors with unknown parameters.

Abstract: Blind multiuser detector can suppress the MAI(multiple address interference) effectively. Gaussian channel noise is assumed in the traditional methods, but the non-Gaussian channel noise is more realistic. This paper proposes a new CMA(Constant Modulus Algorithm) criterion employing FLOS(fractional lower-order statistic). Theoretical analyses and the computer simulations indicate that the associated FLOS-CMA blind MUD(MultiUser Detection) method,based on a stochastic gradient descent algorithm has a good performance in BER(bit error rate). The traditional MUD algorithm is the special case of this algorithm.

Abstract: How fuzzy technology and neural networks and genetic algorithm combine with each other has become the focus of research. A fuzzy neural network controller was proposed based on defuzzification and optimization around the fuzzy neural network structure. Genetic algorithm of fuzzy neural network was brought forward based on optimal control theory. Optimal structure and parameters of fuzzy neural network controller were Offline searched by way of controller performance indicators of genetic algorithm. Fuzzy neural network controller through genetic algorithm was accessed in fuzzy neural network intelligent control system.

Abstract: In this paper, a generalized sub-ODE method is pro-posed to construct exact solutions of Boussinesq equation. As a result, some new exact traveling wave solutions are found.

Abstract: In this paper, we derive exact traveling wave soluti-ons of (2+1) dimensional Boussinesq equation by the known (G’/G) expansion method and a proposed Bernoulli sub-ODE method. We also make a comparison between the two method.

Abstract: In this paper, we derive exact traveling wave soluti-ons of (2+1) dimensional breaking soliton equation by a proposed Bernoulli sub-ODE method. The method appears to be efficient in seeking exact solutions of nonlinear equations. We also make a comparison between the present method and the known (G’/G) expansion method.

Abstract: In this paper, we derive exact traveling wave soluti-ons of (3+1) dimensional potential-YTSF equation by a proposed Bernoulli sub-ODE method. The method appears to be efficient in seeking exact solutions of nonlinear equations. We also make a comparison between the present method and the known (G’/G) expansion method.