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Almost periodic solutions for a memristor-based neural networks with leakage, time-varying and distributed delays

Neural networks : the official journal of the International Neural Network Society 2015年 68卷 34-45页

作者： Ping Jiang Zhigang Zeng Jiejie Chen School of Automation Huazhong University of Science and Technology Wuhan 430074 China School of Computer Science and Technology Hubei PolyTechnic University Huangshi 435003 China. Electronic address: jiangping20140209@***. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: hustzgzeng@***. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China.

In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function method, we prove that this delayed neural network has a unique almost periodic solution, which is globally exponentially stable. Moreover, the obtained conclusion on the almost periodic solution is applied to prove the existence and stability of periodic solution (or equilibrium point) for this delayed neural network with periodic coefficients (or constant coefficients).

关键词： Almost periodic solution Global exponential stability Leakage Memristor-based neural networks Time-varying and distributed delays

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Parallel programming in spiking neural P systems with synapses states

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Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3418-3423页

作者： Yuan, Kong Dongming, Zhao School of Automation Wuhan University of Technology Wuhan Hubei China Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei China

Spiking neural P systems with synapses states characterize the movement of spikes among the neurons. The number of the spikes in neurons can be represented by integers, which provide a way to represent increment, decrement, relational operations and assignment statement using spiking neural P systems with synapses states. According to these basic structures, it is possible to represent programming languages constructs. In this work, a kind of parallel programming language dealing with integer variables is considered, and it is simulated by spiking neural P systems with synapses states. Copyright © 2015 American Scientific Publishers.

关键词： Parallel programming

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Application of multi-gene genetic programming based on separable functional network for landslide displacement prediction

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Neural Computing and Applications 2015年第6期27卷 1771-1784页

作者： Chen, Jiejie Zeng, Zhigang Jiang, Ping Tang, Huiming School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China Faculty of Engineering China University of Geosciences Wuhan China

Complexity of analysis of landslide hazard is due to uncertainty. In this study, a novel approach multi-gene genetic programming based on separable functional network (MGGPSFN) is presented for predicting landslide displacement. Moreover, Pearson's cross-correlation coefficients and mutual information are adopted to look for the potential input variables for a forecast model in the paper. The performance of new model is verified through one case study in Baishuihe landslide in the Three Gorges Reservoir in China. In addition, we compared it with two methods, back-propagation neural network and radial basis function, and MGGPSFN got the best results in the same measurements.

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New results on anti-synchronization of switched neural networks with time-varying delays and lag signals

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Neural networks : the official journal of the International Neural Network Society 2016年 81卷 52-8页

作者： Yuting Cao Shiping Wen Michael Z Q Chen Tingwen Huang Zhigang Zeng School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: wenshiping226@***. The Department of Mechanical Engineering The University of Hong Kong Hong Kong. Texas A & M University at Qatar Doha 5825 Qatar.

This paper investigates the problem of global exponential anti-synchronization of a class of switched neural networks with time-varying delays and lag signals. Considering the packed circuits, the controller is dependent on the output of the system as the inner states are very hard to measure. Therefore, it is necessary to investigate the controller based on the output of the neuron cell. Through theoretical analysis, it is obvious that the obtained ones improve and generalize the results derived in the previous literature. To illustrate the effectiveness, a simulation example with applications in image encryptions is also presented in the paper.

关键词： Anti-synchronization Exponential stability Switched neural networks

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The finite languages generated by spiking neural P systems with astrocytes

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Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3294-3298页

作者： Yuan, Kong Kai, Zhang Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei China School of Computer Science Wuhan University of Science and Technology Wuhan Hubei China

Spiking neural P systems with astrocytes (SNPA, for short) are a class of distributed parallel computing devices inspired from the way spikes pass through the synapses between the neurons. In the present work, we discuss the computing power of SNPA systems as language generators, with special emphasis on the finite languages generated by SNPA systems. It is found that the finite languages of special forms can be generated by SNPA systems, while these languages cannot generated by spiking neural P systems without astrocytes. Copyright © 2015 American Scientific Publishers.

关键词： Computing power

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A new automatic mass detection method for breast cancer with false positive reduction

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Neurocomputing 2015年 152卷 388-402页

作者： Xiaoming Liu Zhigang Zeng School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430081 China

Mass localization is a crucial problem in computer-aided detection (CAD) system for the diagnosis of suspicious regions in mammograms. In this paper, a new automatic mass detection method for breast cancer in mammographic images is proposed. Firstly, suspicious regions are located with an adaptive region growing method, named multiple concentric layers (MCL) approach. Prior knowledge is utilized by tuning parameters with training data set during the MCL step. Then, the initial regions are further refined with narrow band based active contour (NBAC), which can improve the segmentation accuracy of masses. Texture features and geometry features are extracted from the regions of interest (ROI) containing the segmented suspicious regions and the boundaries of the segmentation. The texture features are computed from gray level co-occurrence matrix (GLCM) and completed local binary pattern (CLBP). Finally, the ROIs are classified by means of support vector machine (SVM), with supervision provided by the radiologist׳s diagnosis. To deal with the imbalance problem regarding the number of non-masses and masses, supersampling and downsampling are incorporated. The method was evaluated on a dataset with 429 craniocaudal (CC) view images, containing 504 masses. Among them, 219 images containing 260 masses are used to optimize the parameters during MCL step, and are used to train SVM. The remaining 210 images (with 244 masses) are used to test the performance. Masses are detected with 82.4% sensitivity with 5.3 false positives per image (FPsI) with MCL, and after active contour refinement, feature analysis and classification, it obtained 1.48 FPsI at the sensitivity 78.2%. Testing on 164 normal mammographic images showed 5.18 FPsI with MCL and 1.51 FPsI after classification. Experiments on mediolateral oblique (MLO) images have also been performed, the proposed method achieved a sensitivity 75.6% at 1.38 FPsI. The method is also analyzed with free response operating characteristi

关键词： Mass detection Breast cancer Level set Local binary pattern Support vector machine

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Observer-Based Robust Coordinated Tracking of Multi-Agent Systems with Input Saturation

Observer-Based Robust Coordinated Tracking of Multi-Agent Sy...

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IEEE Annual Conference on Decision and control

作者： Xiaoling Wang Housheng Su Xiaofan Wang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781479978878

This paper addresses the robust semi-global coordinated tracking problem of multiple-input multiple-output (MIMO) multi-agent systems with input saturation and communication noise. A distributed observer-based coordinated tracking protocol is constructed by combining a novel parameterized low-and-high feedback technique with the high-gain observers design approach. It is shown that, under the assumptions that each agent is asymptotically null-controllable with bounded controls and the network is connected, semi-global consensus tracking or semi-global swarm tracking can be attained for left-invertible and minimal-phase systems.

关键词： noise(communication) bounded control tracking high gain Agents

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A novel method to derive ambulatory blood pressure from the radial pressure waveform

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 472卷 176-181页

作者： He, Long Chen, Zhihua Zhang, Zheng Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)9783662450482

In this paper, we develop a novel application of independent component analysis (ICA) based auto-regression forecasting model(ICAARF). The method can noninvasively, continuously and conveniently derive ambulatory blood pressure (ABP) from the radial artery pressure waveform (RAPWF). To eliminate the effect of correlative factors in measurement, the ICA method is used to decomposite the raw signal and extract the independent component affected by blood pressure (BP). Based on the spectrum density of independent component, an auto-regression forecasting model is set up to derive BP. Experimental results show an excellent correlation and agreement with the BP measured by Omron electronic BP monitor (Type: HEM-7012). If the ICA-ARF is used, the the error can be reduced from 7.4mmHg to 2.55mmHg. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Blood pressure

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A heuristically accelerated multi-agent reinforcement learning algorithm applied to flow line maintenance scheduling

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Journal of Computational Information Systems 2015年第6期11卷 2245-2255页

作者： Wang, Xiao Wang, Hongwei Qi, Chao Wang, Xu School of Safety Engineering Shenyang Aerospace University Shenyang China Institute of Systems Engineering/State Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

This paper investigates the maintenance scheduling problem in a flow line system consisting of two series machines with a finite buffer in between. The machines deteriorate with age and have multiple deteriorating quality states represented by multiple decreasing yield levels. The maintenance problem of both machines is modeled as semi-Markov decision processes. A heuristically accelerated multi-agent reinforcement learning algorithm with a feature of incorporating heuristic function for action selection is developed to produce a reasonable maintenance scheduling. A comparison with a Ε-greedy search based exploration algorithm, a simulated annealing search based exploration algorithm, a tabu search based exploration algorithm and a neighborhood search based exploration algorithm in reinforcement learning is presented. The results indicate that the proposed heuristically accelerated multi-agent reinforcement learning algorithm is competitive and has a certain advantage for larger problems. Copyright © 2015 Binary Information Press.

关键词： Tabu search

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A new crossbar architecture based on two serial memristors with threshold

A new crossbar architecture based on two serial memristors w...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiaoping Wang Min Chen Yi Shen Xiaoya Hu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China School of Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781479919611

This paper presents a memory crossbar based on two serial memristors with threshold characteristic to eliminate the effect of sneak paths, which is a key issue in crossbar memory system leading to great degradation in their performance and power efficiency. At first, we analyze the threshold characteristic of memristor and propose a memristor model with threshold. Based on this model, the paper presents the design and simulation of a non-volatile memory system utilizing two serial memristors with different polarities as a memory cell. This scheme solves the sneak-path problem by taking advantage of the threshold characteristic and the performance with having always high resistance state in all the memory cells, which is validated by simulation results. The scheme also possesses the superior properties of remarkable compatibility and high density.

关键词： Memristors Nonvolatile memory

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