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Identifying Driver Nodes in the Human Signaling Network Using Structural controllability Analysis

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2015年第2期12卷 467-472页

作者： Liu, Xueming Pan, Linqiang Huazhong Univ Sci & Technol Sch Automat Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

Cell signaling governs the basic cellular activities and coordinates the actions in cell. Abnormal regulations in cell signaling processing are responsible for many human diseases, such as diabetes and cancers. With the accumulation of massive data related to human cell signaling, it is feasible to obtain a human signaling network. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis to biological networks. In this work, we apply structural controllability to a human signaling network and detect driver nodes, providing a systematic analysis of the role of different proteins in controlling the human signaling network. We find that the proteins in the upstream of the signaling information flow and the low in-degree proteins play a crucial role in controlling the human signaling network. Interestingly, inputting different control signals on the regulators of the cancer-associated genes could cost less than controlling the cancer-associated genes directly in order to control the whole human signaling network in the sense that less drive nodes are needed. This research provides a fresh perspective for controlling the human cell signaling system.

关键词： Human signaling network controllability driver node

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Observer-based robust control for a flexible launch vehicle

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND control ENGINEERING 2015年第6期229卷 506-516页

作者： Ou, Liuli Liu, Lei Wang, Yongji Huang, Jian Huazhong Univ Sci & Technol Key Lab Minist Educ Image Proc & Intelligent Control Sch Automat Wuhan 430074 Peoples R China

This article investigates the problem of robust stabilization for a flexible launch vehicle. Since the launch vehicle suffers from parametric uncertainties, bending modes, and external wind disturbances simultaneously, an observer-based methodology is provided to address these negative factors. The proposed method can guarantee the stability of the closed-loop system and minimize the H performance index. Additional regional pole placement constraints are imposed on the feedback gain matrices to improve the transient performance of the system. A two-step strategy is proposed to solve the involving bilinear matrix inequality problem. Compared with existing methods, which mainly depend on introducing additional constraints to linearize the bilinear matrix inequality conditions, the proposed strategy can reduce the conservatism and is suitable for engineering practice. The simulation results for one operating point and nonlinear model illustrate the validity and effectiveness of the proposed control method.

关键词： Interval uncertainties H-infinity observer robust control bending mode linear matrix inequality regional pole placement quadratic matrix inequality

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Counteracting the dynamical degradation of digital chaos via hybrid control

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2014年第6期19卷 1970-1984页

作者： Hu, Hanping Deng, Yashuang Liu, Lingfeng Huazhong Univ Sci & Technol Sch Automat Educ Minist Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

Chaotic systems would degrade owing to finite computing precisions, and such degradation often seriously affects the performance of digital chaos-based applications. In this paper, a chaotification method is proposed to solve the dynamical degradation of digital chaotic systems based on a hybrid structure, where a continuous chaotic system is applied to control the digital chaotic system, and a unidirectional coupling controller that combines a linear external state control with a modular function is designed. Moreover, we proof rigorously that a class of digital chaotic systems can be driven to be chaotic in the sense that the system is sensitive to initial conditions. Different from the existing remedies, this method can recover the dynamical properties of system, and even make some properties better than those of the original chaotic system. Thus, this new approach can be applied to the fields of chaotic cryptography and secure communication. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Digital chaotic system Dynamical degradation Chaotification Complexity

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Memristor-based circuit implementation of Competitive Neural Network based on online unsupervised Hebbian learning rule for pattern recognition

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NEURAL COMPUTING & APPLICATIONS 2022年第1期34卷 319-331页

作者： Li, Mian Hong, Qinghui Wang, Xiaoping Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

In this paper, a Competitive Neural Network circuit based on voltage-controlled memristors is proposed, of which the synapse structure is one memristor (1M). The designed circuit consists of the forward calculation part and the weight updating part. The forward calculation part is designed according to the winner-take-all mechanism, in which the m-LIF model and PMOS transistors with switching characteristics are combined to achieve the lateral inhibition. The weight updating part is designed based on the Hebbian learning rule. By using the voltage controlled switches, only the synaptic memristors connected to the winner output neuron obtained from the forward calculation part are adjusted. The whole circuit does not require the participation of CPU, FPGA or other microcontrollers, providing the possibility to realize computing-in-memory and parallel computing. We perform simulation experiments of unsupervised online learning of 5*3 pixels patterns and 28*28 pixels patterns based on the designed circuit in PSPICE. The changing trend of the network weights during the training phase and the high recognition accuracy in the recognition phase verify the network can effectively learn and recognize different patterns.

关键词： Memristive circuit Competitive Neural Network Unsupervised learning Winner-take-all Pattern recognition

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Memristor-based BAM circuit implementation for image associative memory and filling-in

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NEURAL COMPUTING & APPLICATIONS 2021年第13期33卷 7929-7942页

作者： Yang, Zijia Wang, Xiaoping Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China

Associative memory and filling-in are two essential functions of the human brain. To implement these two brain-inspired functions in hardware, we proposed a memristor-based bidirectional associative memory (BAM) circuit in this paper. This circuit combines an online algorithm with a memristor array adjustment process, thus makes the circuit more universal for various tasks. The proposed circuit is constructed out of memristive synaptic circuits, IN modules and ACT modules. The memristive synaptic circuits utilize memristor arrays to represent weight matrix and operate corresponding operations hence make computing-in-memory and process information in parallel, which simplifies the complexity of circuit and improves the processing speed. The IN modules employ transistors as switches to choose the input layer hence can get initial information flow bidirectionally. The ACT modules perform activation function and can output continuous arbitrary real numbers. Thereby, both binary and gray-scale images can be tested in the proposed circuit. In addition to the hetero-association and filling-in results given in detail, the retrieval rates of the proposed circuit with the impact of different degrees of noise and the number of stored patterns are also evaluated and compared with software-based BAM. The simulation has experimented via MATlab and PSpice, and the corresponding results show a remarkable performance of the proposed circuit. The influence of memristor's stuck-at-fault is also considered. In comparison with software-based BAM and similar memristor-based neural network circuit, the proposed circuit performs better in processing speed.

关键词： Memristors Bidirectional associative memory Associative memory Filling-in

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Minimum time state consensus for cooperative attack of multi-missile systems

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AEROSPACE SCIENCE AND TECHNOLOGY 2017年 69卷 87-96页

作者： Liu, Xing Liu, Lei Wang, Yongji Huazhong Univ Sci & Technol Sch Automat Key Lab Minist Educ Image Proc & Intelligent Control Wuhan Hubei Peoples R China

This paper considers the cooperative attack with multiple missiles on a stationary target and a two-step procedure is proposed. First the states of all missiles are guided to achieve minimum time consensus, and then, by using the proportional navigation guidance law with identical navigation gain each missile arrives at the target simultaneously or sequentially. Among which, the strategy to realize state consensus in minimum time is the focus of the issue. In the paper the coordination algorithms are developed based on bang-bang control strategy due to its simply structure, subsequently, it is proved that the time optimal consensus problem can be transformed into a parameter optimization problem. Besides, the proposed schemes are able to significantly reduce the number of parameters to be optimized and finally solve the problem with little computation cost. Different from the impact time control methods, the strategy for state consensus does not demand the information of time-to-go. Meanwhile only the initial values of missiles' states are required for the coordination algorithms which lead to less communication burden. Two different examples are provided to demonstrate the validity and efficiency of our proposed strategy. (C) 2017 Elsevier Masson SAS. All rights reserved.

关键词： Cooperative attack Multiple missiles Minimum time consensus State synchronization

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Memristive Circuit Design of Brain-Like Emotional Learning and Generation

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IEEE TRANSACTIONS ON CYBERNETICS 2023年第1期53卷 222-235页

作者： Wang, Zilu Wang, Xiaoping Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

In this work, a bionic memristive circuit with the functions of emotional learning and generation is proposed, which can perform brain-like emotional learning and generation based on various types of input information. The proposed circuit is designed based on the brain emotional learning theory in the limbic system, which mainly includes three layers of design: 1) the bottom layer is the design of the basic unit modules, such as neuron and synapse;2) the middle layer is the design of the functional modules related to emotional learning in the limbic system, such as the amygdala, thalamus, and so on;and 3) the top layer is the design of the overall circuit, which is used to realize the function of the emotional generation. A 2-D emotional space composed of valence and arousal signals is adopted. According to the above bottom-up circuit design method, the valence and arousal signals can be generated, respectively, by designing corresponding emotional learning circuits, so as to form continuous emotions. The volatile and nonvolatile memristors are mainly used to mimic the functions of the neuron and synapse at the bottom layer of the circuit to achieve the core emotional learning function of the middle layer, thereby constructing a brain-like information processing architecture to realize the function of the emotional generation in the top layer. The simulation results in PSPICE show that the proposed circuit can learn and generate emotions like humans. If the proposed circuit is applied to a humanoid robot platform through further research, the robot may have the ability of personalized emotional interaction with humans, so that it can be effectively used in emotional companionship and other aspects.

关键词： Memristors Neurons Brain Synapses Limbic system Integrated circuit modeling Biological system modeling 2-D emotional space circuit implementation emotional learning and generation limbic system memristor

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An RFID-based digital warehouse management system in the tobacco industry: a case study

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2010年第9期48卷 2513-2548页

作者： Wang, Hongwei Chen, Shuang Xie, Yong Huazhong Univ Sci & Technol Inst Syst Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

This paper proposes a digital warehouse management system (DWMS) in the tobacco industry based on radio frequency identification (RFID) technology. The DWMS helps warehouse managers to achieve better inventory control, as well as to improve the operation efficiency. In this system, a set of basic events and storage/retrieval rules are defined as event-condition-action (ECA) rules to improve the feasibility and flexibility of DWMS. By using RFID technology, the DWMS enables a plane warehouse to achieve visualised inventory management, automatic storage/retrieval assignment and high accuracy of inventory control as an automatic warehouse. A case in the tobacco industry is studied to illustrate the feasibility and rationality of the proposed system. Based on the ECA rules, a storage/retrieval methodology is proposed to improve the storage/retrieval operations. The results of this case study illustrate that RFID-DWMS can help a plane warehouse to improve operation efficiency, enhance the utilisation of warehouse capacity, increase inventory accuracy and reduce manpower and loading time significantly.

关键词： radio frequency identification digital warehouse management system storage/retrieval assignment event-condition-action digital pallet digital shelf

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Analysis and design of associative memories based on recurrent neural network with discontinuous activation functions

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NEUROCOMPUTING 2012年第1期77卷 101-107页

作者： Bao, Gang Zeng, Zhigang Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Hubei Peoples R China

This paper considers a recurrent neural network (RNN) with a special class of discontinuous activation function which is piecewise constants in the state space. One sufficient condition is established to ensure that the novel recurrent neural networks can have (4k-1)" locally exponential stable equilibrium points. Such RNN is suitable for synthesizing high-capacity associative memories. The design procedure is presented with the method of singular value decomposition. Finally, the validity and performance of the results are illustrated by use of two numerical examples. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Multistability Neural network Associative memory

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Tracking performance analysis of flight control system based on H-infinity theory

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND control 2013年第3期19卷 290-298页

作者： Dong, Shuai Wang, Zhisheng Wang, Yongji Liu, Lei Ou, Liuli Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

This paper proposes robust tracking performance criterion for flight control system clearance while other linear methods focus on robust stability criterion or stability margin criterion. The new criterion aims at guarantee of fast and accurate tracking of designated trajectory when flight control system suffers from uncertain parameters. With H-infinity theory, the clearance problem is transformed to a series of linear matrix inequalities on the vertices of parametric space. When the criterion is violated, two adaptive strategies are developed to identify the flyable region in parametric space. The proposed method is performed on a bank-to-turn missile as an example to illustrate the clearance process. Then the clearance result is validated by simulation.

关键词： robust tracking performance LMIs clearance criterion H-infinity parametric uncertainty

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