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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Lan, Xuejing Wang, Zhishen Liu, Lei Wang, Yongji School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783902823625

The H∞ based decoupling tracking control is studied in this paper. A virtual system constituted by the controlled system and the no coupling reference model is firstly set up. The controlled system is driven to follow the reference model to realize the decoupling. And the tracking error can be formulated by the H∞ norm of the virtual system. Then the controller is derived by minimizing the H∞ norm, which can be described by Linear Matrix Inequalities (LMIs). The necessary and sufficient condition of existence of controller is derived based on the LMIs above. A flight control example is given to illustrate the effectiveness of the proposed method. The simulation results show that the proposed method is of better control performance than Linear Quadratic (LQ) tracking controller. © IFAC.

关键词： controllers

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intelligent multi-user detection using an artificial immune system

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Science in China(Series F) 2009年第12期52卷 2342-2353页

作者： GONG MaoGuo, JIAO LiCheng, MA WenPing & MA JingJing 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 Xidian University Xi’an China Institute of Intelligent Information Processing Xidian University Xi’an China

Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.

关键词： artificial immune systems clonal selection multi-user detection code-division multiple-access genetic algorithm

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An optimal software maintenance policy based on reliability and risk

An optimal software maintenance policy based on reliability ...

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2014 International Joint Conference on Neural Networks, IJCNN 2014

作者： Xiaoping, Wang Fang, Zhou Yi, Shen School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479914845

Software maintenance is assuming ever more a crucial role in the lifecycle of software due to the increase of software requirements and the high variability of software environment. Common approaches of studying software maintenance are to consider them as a static by-product of software operation and only the maintenance cost is covered. In this paper, software maintenance policies are studied with the consideration of software reliability and risk. An optimization model is defined to drive the choice of a maintenance schedule. The solution of the model provides the best maintenance policy and the choice of actual actions that will minimize the average maintenance cost while the software reliability and risk are acceptable. Finally, a numerical example is given to show the analysis process of our proposed policy. © 2014 IEEE.

关键词： Software reliability

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Aero-thermal radiation correction via multi-scale bias field estimation 3

Aero-thermal radiation correction via multi-scale bias field...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Li, Lerenhan Yan, Luxin Sang, Nong Gao, Changxin Hu, Jing Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, a multi-scale bias field estimation is proposed to carry out the aero-thermal radiation correction. The bias field is estimated at scales from coarse to fine by an alternative minimization, after which, the degraded image is restored via subtraction. In the minimization, Tiknov regularization is employed to constrain the smoothness of bias field while Total Variation (TV) is adopted to preserve the details and structures of the latent image. Besides, Split Bregman iteration is introduced to conquer the difficulty in the non-smooth problem when resolving the minimization. Compared with conventional approaches, experiments verified that the proposed method contributes to the rapidness and precision of the algorithm. © 2015 IEEE.

关键词： Iterative methods

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DeNet: An explicit distance ensemble model for person re-identification 3

DeNet: An explicit distance ensemble model for person re-ide...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Wang, Jin Gao, Changxin Hu, Jing Sang, Nong Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, we address the problem of person reidentification (re-id), which remains to be challenging due to view point changes, pose variations, different camera settings, etc. Different from common methods that concatenate descriptors extracted from different support regions and feature channels directly as a long vector, we encode the importance of different feature channels and support regions explicitly and propose a two-layer distance ensemble model called DeNet to measure the similarity between two images. The first layer of DeNet combines distances of different support regions while the second layer weights different feature channels. Weight parameters of DeNet are learnt under the large margin framework with the goal of maximizing the difference between distances of positive and negative matching pairs. Our method achieves very competitive results on the widely used VIPeR and PRID 450S datasets. © 2015 IEEE.

关键词： Computers

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Optimal control of switched linear systems based on migrant particle swarm optimization algorithm

Optimal control of switched linear systems based on migrant ...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Xie, Fuqiang Wang, Yongji Zheng, Zongzhun Li, Chuanfeng Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

The optimal control problem for switched linear systems with internally forced switching has more constraints than with externally forced switching. Heavy computations and slow convergence in solving this problem is a major obstacle. In this paper we describe a new approach for solving this problem, which is called Migrant Particle Swarm Optimization (Migrant PSO). Imitating the behavior of a flock of migrant birds, the Migrant PSO applies naturally to both continuous and discrete spaces, in which definitive optimization algorithm and stochastic search method are combined. The efficacy of the proposed algorithm is illustrated via a numerical example. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Hybrid systems

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Spiking Neural Network for Intra-cortical Brain Signal Decoding

arXiv

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arXiv 2025年

作者： Yang, Song Fu, Haotian Zhang, Herui Zhang, Peng Li, Wei Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China Department of Biomedical Engineering College of Life Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Decoding brain signals accurately and efficiently is crucial for intra-cortical brain-computer interfaces. Traditional decoding approaches based on neural activity vector features suffer from low accuracy, whereas deep learning based approaches have high computational cost. To improve both the decoding accuracy and efficiency, this paper proposes a spiking neural network (SNN) for effective and energy-efficient intra-cortical brain signal decoding. We also propose a feature fusion approach, which integrates the manually extracted neural activity vector features with those extracted by a deep neural network, to further improve the decoding accuracy. Experiments in decoding motor-related intra-cortical brain signals of two rhesus macaques demonstrated that our SNN model achieved higher accuracy than traditional artificial neural networks;more importantly, it was tens or hundreds of times more efficient. The SNN model is very suitable for high precision and low power applications like intracortical brain-computer interfaces. © 2025, CC BY.

关键词： Deep neural networks

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NEAT versus PSO for evolving autonomous multi-agents coordination on pursuit-evasion problem

NEAT versus PSO for evolving autonomous multi-agents coordin...

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2011 3rd International Asia Conference on Informatics in control, Automation and Robotics, CAR 2011

作者： Zhao, Jin Peng, Gang Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry China

ISBN: (纸本)9783642259913

A method based on multi-agents and ANN (Artificial Neural Network) was proposed to solve the pursuit-evasion task in continuous time-varying environment. According to this method, several autonomous agents with 8 circular sector sensors and an ANN controller were used to form a coordinated behavior to capture the evaders. To evolve the controller, NEAT (NeuroEvolution of Augmenting Topologies) and PSO (Particle Swarm Optimization) method were used to optimize the network. The simulation experiments show that both methods can successfully evolve the controller to capture the evaders, while NEAT requires less swarm members and consume less time comparing to PSO method. © 2011 Springer-Verlag.

关键词： controllers

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Parallel generate entry landing footprint using differential evolution

Parallel generate entry landing footprint using differential...

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2012 International Symposium on Computer, Consumer and control, IS3C 2012

作者： Chang, Songtao Wang, Yongji Liu, Lei Dep. of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546551

Landing footprint of an entry vehicle provides critical information for mission planning. Conventional methods calculate it through solving a family of multi-constraints optimal control problems. It is difficult to solve. To generate the boundary of it, we proposed a new scheme based on differential evolution(DE). Utilizing DE's parallelism, each run generates one side instead of one point of the boundary. To get the full boundary, just need run the algorithm two times. The algorithm's merits include accurate, fast, not relying on simplification of the system, all control variables are under consideration and facilitating parallel programming. © 2012 IEEE.

关键词： Evolutionary algorithms

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Immune secondary response and clonal selection inspired optimizers

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Progress in Natural Science:Materials International 2009年第2期19卷 237-253页

作者： Maoguo Gong a,Licheng Jiao a,Lining Zhang a,Haifeng Du b a 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 b School of Public Policy and Administration,Xi’an Jiaotong University,Xi’an 710049,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 School of Public Policy and Administration Xi’an Jiaotong University Xi’an 710049 China

The immune system’s ability to adapt its B cells to new types of antigen is powered by processes known as clonal selection and affinity maturation. When the body is exposed to the same antigen,immune system usually calls for a more rapid and larger response to the antigen,where B cells have the function of negative adjustment. Based on the clonal selection theory and the dynamic process of immune response,two novel artificial immune system algorithms,secondary response clonal programming algorithm (SRCPA) and secondary response clonal multi-objective algorithm (SRCMOA),are presented for solving single and multi-objective optimization problems,respectively. Clonal selection operator (CSO) and secondary response operator (SRO) are the main operators of SRCPA and SRCMOA. Inspired by the clonal selection theory,CSO reproduces individuals and selects their improved maturated progenies after the affinity mat-uration process. SRO copies certain antibodies to a secondary pool,whose members do not participate in CSO,but these antibodies could be activated by some external stimulations. The update of the secondary pool pays more attention to maintain the population diversity. On the one hand,decimal-string representation makes SRCPA more suitable for solving high-dimensional function optimiza-tion problems. Special mutation and recombination methods are adopted in SRCPA to simulate the somatic mutation and receptor edit-ing process. Compared with some existing evolutionary algorithms,such as OGA/Q,IEA,IMCPA,BGA and AEA,SRCPA is shown to be able to solve complex optimization problems,such as high-dimensional function optimizations,with better performance. On the other hand,SRCMOA combines the Pareto-strength based fitness assignment strategy,CSO and SRO to solve multi-objective optimization problems. The performance comparison between SRCMOA,NSGA-Ⅱ,SPEA,and PAES based on eight well-known test problems shows that SRCMOA has better performance in converging to approximate Pareto

关键词： Clonal selection Secondary response Artificial immune systems Evolutionary algorithms

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