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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Zhujin Zhang Lin Liu Jiuyong Li Zheng Zhang School of Computer and Information Science University of South Australia Adelaide SA Australia Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

Randić et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation and prove that the claim is correct, and that it also avoids degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the spectral representation. The method adopts M value to characterize a graphical representation and uses 24-component vector as descriptor. The approach is illustrated on the complete coding sequence of beta-globin genes from 7 different species.

关键词： Humans Rabbits Mice Variable speed drives Silicon Sun Bovine

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Multi-channel Hammerstein identification

Multi-channel Hammerstein identification

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作者： Wei, Yue Zhang, Hai-Tao Chen, Michael ZhiQiang Zhou, Tao State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Department of Automation Nanjing University of Science and Technology Nanjing 210094 China Department of Modern Physics University of Science and Technology of China Hefei 230026 China Department of Physics University of Fribourg Chemin du Muse CH-1700 Fribourg Switzerland

ISBN: (纸本)9787894631046

The Hammerstein systems, consisting of a zero-memory nonlinearity followed by a linear dynamic function, exists universally in industrial, chemical, physical and biological systems. Thus an effective modelling method for Hammerstein systems is critical for both relevant scientific research and engineering applications. We propose a novel Hammerstein identification approach, in which a multi-channel mechanism is used to separate the coefficients of the linear and nonlinear blocks more completely. Compared with traditional single-channel identification algorithms, the present identification method can enhance the approximation accuracy remarkably under the weak condition on the persistent excitation (PE) condition of the inputs.

关键词： Singular value decomposition

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ANN based three-value logic SVPWM control in CSR

ANN based three-value logic SVPWM control in CSR

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Jinbang Xu Anwen Zhizhuo Wu Jun Yang Xuan Yang Department of Control Science & Technology Huazhong University of Science & Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science & Technology Huazhong University of Science & Technology 430074 Wuhan China

To achieve better performance with various load and system parameters in controlling a current-source rectifier (CSR) with less computing cost, a neural-network-based implementation of three-logic space-vector modulation (SVM) is proposed in this research, and the random weight change (RWC)algorithm is employed for on-line parameter tuning. The scheme has been simulated in SABER simulation software and the result is compared with the conventional SVM method. The advantage of the method is explicit with a better performance under a non-rated system load.

关键词： Support vector machines Artificial neural networks Computational modeling

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Multiple-atlas-based automatic sementation of hippocampus for lateralization in temporal lobe epilepsy

Multiple-atlas-based automatic sementation of hippocampus fo...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi-Asl Kourosh Jafari-Khouzani Hamid Soltanian-Zadeh Image Analysis Laboratory Department of Diagnostic Radiology Henry Ford Health System Detroit MI USA School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424441259

We introduce a 3D segmentation framework which uses principal shapes. The probabilistic energy function of the method is defined based on intensity, tissue type, and location information of the structures using a multiple atlas method. For intensity information, nonparametric probability density function is used which considers intensity relation of different structures. To find a local minimum of the energy function, a two-step optimization strategy is used. In the first step, shape parameters are optimized based on the analytic derivatives of the energy function. In the second step, shapes of the structures are fine-tuned using a level set method. The proposed method is shown to be superior to some popular methods in the literature using a dataset of 64 patients with mesial temporal lobe epilepsy. In addition, the method can be used for lateralization with accuracy close to that of manual segmentation.

关键词： Hippocampus Temporal lobe Epilepsy image segmentation Principal component analysis Shape control Probability density function Level set Skull Algorithm design and analysis

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Solving NP-complete problems by spiking neural P systems with budding rules

Solving NP-complete problems by spiking neural P systems wit...

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10th International Workshop on Membrane Computing, WMC 2009

作者： Ishdorj, Tseren-Onolt Leporati, Alberto Pan, Linqiang Wang, Jun Computational Biomodelling Laboratory Åbo Akademi University Department of Information Technologies 20520 Turku Finland Università degli Studi di Milano - Bicocca Dipartimento di Informatica Sistemistica e Comunicazione Viale Sarca 336/14 20126 Milano Italy Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Research Group on Natural Computing Department of CS and AI University of Sevilla Avda Reina Mercedes s/n 41012 Sevilla Spain

ISBN: (纸本)3642114660

Inspired by the growth of dendritic trees in biological neurons, we introduce spiking neural P systems with budding rules. By applying these rules in a maximally parallel way, a spiking neural P system can exponentially increase the size of its synapse graph in a polynomial number of computation steps. Such a possibility can be exploited to efficiently solve computationally difficult problems in deterministic polynomial time, as it is shown in this paper for the NP-complete decision problem sat. © 2010 Springer-Verlag.

关键词： Computational complexity

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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IEEE International Conference on Mechatronics and Automation

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan China College of Mechanical Engineering TaiYuan University of Technology TaiYuan China Institute for Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology WuHan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Degradation Atmospheric modeling Optical scattering Optical imaging

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Study on the Method of image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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Immunodominance and clonal selection inspired multiobjective clustering

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Progress in Natural Science:Materials International 2009年第6期19卷 751-758页

作者： Wenping Ma , Licheng Jiao, Maoguo Gong key laboratory of intelligent Perception and image Understanding of the Ministry of Education of China, Institute of intelligent Information processing, Xidian University, Xi’an 710071, China Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

The biological immune system is a highly parallel and distributed adaptive system. The information processing abilities of the immune system provide important insights into the field of computation. Based on immunodominance in the biological immune system and the clonal selection mechanism, a novel data mining method, Immune Dominance Clonal Multiobjective Clustering algorithm (IDCMC), is presented. The algorithm divides an individual population into three sub-populations according to three different measurements, and adopts different evolution and selection strategies for each sub-population. The update of each sub-population, however, is not carried out in isolation. The periodic combination operation of the analysis of the three sub-populations represents considerable advantages in its global search ability. The clustering task is a multiobjective optimization problem, which is more robust with respect to the variety of cluster structures of different datasets than a single-objective clustering algorithm. In addition, the new algorithm can determine the number of clusters automatically, which should identify the most promising clustering solutions in the candidate set. The experimental results, using artificial datasets with different manifold structure and handwritten digit datasets, show that the IDCMC outperforms the PESA-Ⅱ-based clustering method, the genetic algorithm-based clustering technique and the original K-Means algorithm in solving most of the problems tested.

关键词： Artificial immune systems Multiobjective optimization Clustering Unsupervised learning

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A novel quantum-inspired immune clonal algorithm with the evolutionary game approach

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Progress in Natural Science:Materials International 2009年第10期19卷 1341-1347页

作者： Qiuyi Wu,Licheng Jiao,Yangyang Li,Xiaozheng Deng key laboratory of intelligent Perception and image Understanding of Ministry of Education of China,Institute of intelligent Information processing,Xidian University,Xi’an 710071,China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

The quantum-inspired immune clonal algorithm(QICA) is a rising intelligence *** on evolutionary game theory and QICA,a quantum-inspired immune algorithm embedded with evolutionary game(EGQICA) is proposed to solve combination optimization *** this paper,we map the quantum antibody’s finding the optimal solution to player’s pursuing maximum utility by choosing strategies in evolutionary *** dynamics is used to model the behavior of the quantum antibody and the memory mechanism is also introduced in this *** results indicate that the proposed approach maintains a good diversity and achieves superior performance.

关键词： Game theory Evolutionary game Replicator dynamics Quantum-inspired optimization Artificial immune system

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Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling

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中国物理快报（英文版） 2009年第6期26卷 59-62页

作者： CHEN Jian-Rui JIAO Li-Cheng WU Jian-She WANG Xiao-Hua Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligence Information ProcessingXidian UniversityXi'an 710071 College of Science Inner Mongolia University of TechnologyInner Mongolia 01 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligence Information ProcessingXidian UniversityXi'an 710071

A new general network model for two complex networks with time-varying delay coupling is *** we investigate its synchronization *** two complex networks of the model differ in dynamic nodes,the number of nodes and the coupling *** using adaptive controllers,a synchronization criterion is *** examples are given to demonstrate the effectiveness of the obtained synchronization *** study may widen the application range of synchronization,such as in chaotic secure communication.

关键词： No English keywords

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