Advanced Materials Research Vols. 846-847

Abstract: Ray casting algorithm is a kind of widely used volume rendering algorithm in the field of medical 3D reconstruction. One of the greatest advantages of it is the high rendering quality, while the rendering speed is rather low. In order to accelerate the rendering speed, in this paper, it proposed an accelerated ray casting algorithm which is based on the proximate cloud algorithm, combined with empty voxel leaping and fast interpolation. Meanwhile, it also analyzed the complexity of computing to significantly enhance the speed of the algorithm on volume rendering.

Abstract: This paper aimed at the chaotic synchronization ability of complex networks with different structures whose nodes have different orders. Problems of complex network synchronization and biological application are introduced firstly. And then, we studied synchronization with different orders and different network structures. Based on Lyapunov stability theory, the coupling function of the connecting nodes synchronization is identified. Numerical simulation results were used to compare the synchronization ability of three kinds of network structures. So, certain biological phenomena of complex network can be explained due to our research.

Abstract: The study presents a method to separate the fetal electrocardiograph (FECG) from concomitant maternal electrocardiograph (MECG) by using Fast Independent component analysis (ICA) algorithm of Blind Signal Separation. Current methods of extracting fetal ECG have defects and drawbacks. Traditional ICA method has a persistent problem that the signal of FECG extracted from MECG was always mixed with the signal of MECG in diverse levels, and the order of MECG and FECG is uncertain, resulting in the decrease of its rate of convergence. To improve the rate of convergence, this research adopts Fast ICA algorithm. Experimental results indicate that this method is useful for extracting the fetal signal of ECG. And a satisfactory signal to noise ratio (SNR) is obtained.

Abstract: Bit-interleaved coded modulation iterative decoding (BICM-ID) is an excellent bandwidth efficient transmission scheme,which owns remarkable bit-error-rate (BER) performance both in additive Gaussian noise (AWGN) channel and Rayleigh fading channel.But it leads to the increase of computational complexity and decoding delay at the receiver at the same time. In order to decrease the unnecessary iterations ,a variety of the stopping criteria are put forward . This paper presents an improved simplified cross-entropy (CE) stopping criterion based on Simplified-CE criterion, which calculates the value of CE just one time when Signal to Noise Ratio (SNR) is under 2dB to simplified the iterative process. Simulation results show that the improved Simplified-CE criterion can own the least iterative number when the SNR is under 2dB.And when the SNR is from 2.5dB to 4dB, it is about 12% less than CE criterion in the average iterative numbers.

Abstract: Segmentation of motion in an image sequence is one of the most challenging problems in image processing. In image analysis engineering, accurate statistics of sport image is one of the most important subjects, while at the same time one that finds numerous applications. In this paper, we propose a robust multi-layer background subtraction technique which takes advantages of local texture features represented by local binary patterns (LBP) and photometric invariant color measurements in RGB color space. Due to the use of a simple layer-based strategy, the approach can model moving background pixels with quasiperiodic flickering as well as background scenes which may vary over time due to the addition and removal of long-time stationary objects, which plays an important role in optimizing the growth conditions of sport image. Segmentation of sport images is successfully realized by means of multi-layer background subtraction method and then the sport image is computed precisely.

Abstract: Traffic analysis and forecast are the classic topics of telecommunication research, as they provide strategic ground to address the issues such as mobile networks traffic jam, network coverage planning design, marketing management etc. On the basis of the empirical mode decomposition theory and methods, this article first implements multi-scale analysis of the time series of traffic, then it goes on to executes RBF neural network based on the different compositions, and finally reach the forecast expectation of voice traffics of selected base stations.

Abstract: We present a fifth-order iterative method for the solution of nonlinear equation. The new method is based on two ordinary methods, which are modified Newton methods without second derivatives. Its efficiency index is 1.37973 which is better than that of Newton's method. Numerical results show the efficiency of the proposed method.

Abstract: In this paper,the new compactness which is strong-compactness is introduced for an arbitrary-subset and for a complete distributive De Morgan algebra. The strong-compactness implies strong-III-compactness,hence it also implies strong-II-compactness,strong-I-compactness,-compactness,-compactness and Lowen's fuzzy compactness. But it is different from-compactness.When ,strong-compactness is equivalent to-compactness.

Abstract: ECOC based multi-class classification has been a topic of research interests for many years. Yet most of the previous studies concentrated only on different coding and decoding strategies aiming at improvement over classification accuracies. In this paper, the classification reliability is addressed. By applying the Random Subspace method, a base classifier is created for each of the coding position. The improvement over classification accuracy on each of the coding position is achieved by a reject option and decision fusion. By rejection of those low-confidence samples, the systems reliability is enhanced. The performance of the proposed system was demonstrated by a vehicle classification example, showing promising results.

Abstract: In this paper, we investigate additive properties for the generalized Drazin inverse of bounded linear operators on Banach space . We give explicit representation of the generalized Drazin inverse in terms of under some conditions.