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Chaotic sequences have been widely used as pseudorandom sequences. But the problem of how to judge their autocorrelation function's performances are good or not, up to now, have not been solved. In the paper, by method of phase space, we studied the autocorrelation function of chaotic sequence and discovered that their performance is determined by whether its phase space trajectory is axis symmetrical...
Protein subcellular localization prediction is important to functional annotation of protein. In this study, a hybrid system based on the sorting mechanism of protein was proposed to predict protein subcellular localization. At first, an unknown protein sequence was divided into two sub-sequences at certain position, then features were extracted from them and combined into a fusion feature vector...
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regularization on LDA. The labeled data points provide labeling information and the unlabeled data points provide extra geometric structure information of the data, then we learn a labeling function which is as smooth as possible...
The first hitting time (FHT) plays an important role in convergence evaluation for evolutionary algorithms. However, the current criteria of the FHT are mostly under a hypothesis that never has been testified: the FHT subjects to the normal distribution. Aiming at more convincible evaluations, this paper investigates the distribution of the FHT through a goodness-of-fit test and discovers an unexpected...
Kernel approach has been employed to solve classification problem with complex distribution by mapping the input space to higher dimensional feature space. However, one of the crucial factors in the kernel approach is the choosing of kernel parameters which highly affect the performance and stability of the kernel-based learning methods. In view of this limitation, this paper adopts the eigenvalue...
In this paper, an orthogonal local search genetic algorithm (OLSGA) is proposed for the design and optimization of power electronic circuits. The genetic algorithm is accelerated with a fast local search operator that automatically adjusts the search direction and the step size. An experimental design method called orthogonal design is used to determine the most promising direction of the potential...
A problem of stabilization of cluster unit in wireless sensor and actor network is discussed in this paper. Through modeling WSAN (wireless sensor and actor network) as a new multiple input single output model, this problem is transferred to stabilization of multi-sensor and single controller system with long but bounded multiple random time-delay and packet-loss. Using theories of jump linear system,...
This paper addresses the segmentation problem in noisy image based on Fast Edge Integration (FEI) method in active contour model (ACM) and proposes a new statistical active contour model (SACM). Two modifications are performed in FEI method. First, in order to handle noisy images, maximum log-likelihood estimation is used to replace the minimal variance term proposed by Chan and Vese. Second, a penalising...
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