Advanced Materials Research Vols. 989-994

Abstract: This paper propose a new multiplexing technique which use the bipolar RZ signal to realize duty cycle division multiplexing (DCDM) ,we call it Absolute Polar Duty Cycle Division Multiplexing (APDCDM).Multiplexing and demultiplexing principle of APDCDM are analyzed. Here we have designed a optical fiber transmission system based on APDCDM of three users by Joint simulation with Optisystem and Matlab. Simulation result shows the feasibility of this system. By the analysis of signal energy, explain APDCDM can carry more users than DCDM.

Abstract: A tracking algorithm based on improved Camshift and Kalman filter is proposed in this paper to deal with the problems in traditional Camshift algorithm, such as tracking failure under color interference or occlusion. Firstly, the proposed algorithm improves the single color target model and presents a novel target model, which fuses color and motion cues, to enhance the robustness and accuracy of target tracking. And in order to increase the tracking efficiency, the algorithm combines Kalman filter with the improved Camshift algorithm by using Kalman filter to predict the position of the tracking target under color noises and occlusion. The experiment results demonstrate that the proposed algorithm can track the target object accurately and has better robustness.

Abstract: In this paper, the problem of maximizing the average throughput of a CRN through setting proper sensing sequences is investigated. In order to find the optimal sensing matrix, we obtain the spectrum sensing sequence. The structure of the proposed scheme is discussed in detail.

Abstract: The central step of de-noising in wavelet domain is the threshold selection. To get the best de-noising result, the threshold should be selected according to the noisy observation. This paper presents a genetic adaptive threshold method, which gets the optimum threshold in the sense of least MSE by using an estimation function of the signals’ MSE function. The simulation results with standard wavelet test signals shows that the operation speed of the proposed method four times the traditional continuous searching algorithm, moreover, the optimum threshold calculated is more accurate and reasonable.

Abstract: Based on the helix and-sheet and the-turn conformational parameters, and and , of the 20 amino acids, we propose a new 3D graphical representation of protein sequence without circuit or degeneracy, which may reflect the innate structure of the protein sequence. Then the numerical characterizations of protein graphs, the leading eigenvalues of the L/L matrices associated with the graphical curves for protein sequences, was utilized as descriptors to analyze the similarity/dissimilarity of the nine ND5 protein sequences.

Abstract: A novel adaptive image feature reduction approach for object tracking using vectorized texture feature is proposed in this paper. Our contributions are three-fold: 1) a statistical discriminative appearance model using texture feature was proposed. 2) Majority of dimensions of the features are removed by judging their errors of the chosen distribution model. The remaining dimensions are most discriminative ones for classification task. The dimension reduction has advantages of reducing the computational cost in classification stage. 3) An adaptive learning rate was proposed to handle drifts caused by long term occlusion. Preliminary experimental results are satisfactory and compared to state-of-the-art object tracking methods.

Abstract: Blind source extraction (BSE) is a promising technique to solve signal mixture problems while only one or a few source signals are desired. In biomedical applications, one often knows certain prior information about a desired source signal in advance. In this paper, we explore specific prior information as a constrained condition so as to develop a flexible BSE algorithm. One can extract a desired source signal while its normalized kurtosis range is known in advance. Computer simulations on biomedical signals confirm the validity of the proposed algorithm.

Abstract: As a famous one-unit algorithm, FastICA can extract source signals one by one. In many applications, someone is only interested in a specific source signal. Through incorporating reference about the desired signal into a negentropy based contrast function, a constrained optimization problem is formed. Then an improved method is proposed which can extract the desired source signal exclusively. Computer simulations demonstrate its good performance.

Abstract: According to the problem that the traditional remote sensing image classification methods focus only on analyzing the spectral features and have low utilization of the spatial information, a new spatial-spectral classification method is proposed in this paper, its core idea is to combine the spectral features base on the Principal Component Analysis (PCA) algorithm with the spatial features extracted by the Gabor filter. Experiments show that, compared with the traditional classification methods, the proposed method can improve the classification accuracy and the Kappa coefficient, which means to bring better classification and visual effects.

Abstract: Based on the good correlation and randomness of chaos, this paper uses hybrid Bernouli and Logistic chaotic maps to increase the complexity of chaos, at the same time, we do a combination of discrete frequency coded of non full code sets and poly phase coded, and then hybrid modulation waveforms base on hybrid chaos is proposed for MIMO radar. On the basis of the expression of average ambiguity function is derived, the average fuzzy characteristics of signal waveforms and orthogonality are analyzed in theory. Finally, numerical simulation results validate the correctness of the analysis and the reliability of the signal model.