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A small universal spiking neural P system with communication on request

NEUROCOMPUTING 2018年 275卷 1622-1628页

作者： Pan, Tong Shi, Xiaolong Zhang, Zheng Xu, Fei Huazhong Univ Sci & Technol Sch Automat Educ Minist China Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

Spiking neural P systems (SN P systems, for short) are known as a class of distributed parallel computing models, which are inspired by the way in which neurons process and communicate information with each other by means of spikes. In this work, we focus on a new variant of SN P systems, namely spiking neural P systems with communication on request (SNQ P systems, for short). We concentrate on searching for a small universal SNQ P system. The best known result is that 49 neurons are enough for constructing a Turing universal SNQ P system. Here, we construct a Turing universal SNQ P system with only 14 neurons, which answers an open problem whether the number of neurons for constructing a Turing universal SNQ P system can be further improved. (c) 2017 Elsevier B.V. All rights reserved.

关键词： Bio-inspired computing Membrane computing Spiking neural P system Register machine Universality

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Consensus of Delayed Fractional-Order Multiagent Systems With Intermittent Sampled Data

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2020年第6期16卷 3828-3837页

作者： Ye, Yanyan Su, Housheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan 430074 Peoples R China

In this article, the consensus problem for the delayed fractional-order multiagent system (FOMAS) under directed graph is addressed by intermittent sampled-data control. First, an intermittent sampled-data control protocol with input time delay is proposed. By virtue of Laplace transform and stability theory, some necessary and sufficient conditions depending on the order, input time delay, sampling period, communication width, coupling strengths, and network structure are presented for the delayed FOMASs to reach consensus. Moreover, due to the relationship about the input time delay, communication width, and sampling period, four cases are carefully discussed to find that the sampling period has bounds for a given network with known input time delay and communication width to obtain consensus. Finally, some simulation examples are shown to verify the theoretical results.

关键词： Delay effects Laplace equations Multi-agent systems Protocols Eigenvalues and eigenfunctions Informatics Stability analysis Consensus fractional-order input time delay intermittent sampled-data control multiagent system

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Cascading failures in interdependent directed networks under localized attacks

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2023年 620卷

作者： Lv, Mengyu Pan, Linqiang Liu, Xueming Huazhong Univ Sci & Technol Inst Artificial Intelligence Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Wuhan Peoples R China

Many real-world systems interact with one another through dependency links, which reduces the system robustness. Most previous studies on the robustness of interdependent networks focus on undirected networks, and the related studies on directed networks are limited to random or targeted attacks. However, some failure scenarios cannot be described by these two kinds of attacks, such as earthquakes, floods, and epidemics, where systems are attacked in a local range. In this work, we develop a theoretical framework for analyzing the robustness of interdependent directed networks under localized attacks. We find that for degree homogeneous networks, network robustness under localized attacks is similar to that under random attacks. There are four phase transitions in the phase diagram of the network, and a four-phase transition point and a two-phase transition point are found. For degree heterogeneous networks, localized attacks are more likely to lead to collapse than random attacks. As the coupling strength between networks increases, the interdependent networks first show a second order phase transition, and then a hybrid phase transition, and a first order phase transition at last. Furthermore, as the degree heterogeneity increases, the robustness of networks first increases and then decreases, showing a local robustness maximum. The findings could help understand network robustness and enable better design of robust interdependent systems.

关键词： Localized attack Interdependent networks Directed networks Robustness Percolation theory

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Recovering unknown topology in a two-layer multiplex network:One layer infers the other layer

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Science China(Technological Sciences) 2022年第7期65卷 1493-1505页

作者： LIU Hui SHANG ZhiCheng REN ZiYi LI Yan ZENG ZhiGang LU JunAn School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China School of Mathematics and Statistics Wuhan UniversityWuhan 430072China

There have been increasing interests in studying multiplex dynamical networks *** paper focuses on topology identiflcation of two-layer multiplex networks with peer-to-peer interlayer *** a two-layer network model in which different layers have different coupling patterns,we propose novel methods to recover unknown topological structure of one layer,using the information of the other layer known as a *** proposed methods make full use of the measured evolutional states of the multiplex network itself,and treat the layer with a known structure as an auxiliary layer which is designed to identify the unknown topological *** with the traditional synchronization-based identiflcation method,the proposed methods are in no need of constructing an additional auxiliary network to identify the unknown topological layer,and thus greatly reduce the cost of topology ***,numerical simulations validate the effectiveness of the proposed methods.

关键词： multiplex network synchronization topology identiflcation

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Robust PolInSAR optimal interferogram estimation method based on generalized scattering vector

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Journal of Systems Engineering and Electronics 2017年第3期28卷 457-471页

作者： Zhiyong Suo Ming Li National Lab of Radar Singal Processing Xidian UniversityXi’an 710071China Beijing Aerospace Automatic Control Institute Beijing 100854China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing 100854China

For the polarimetric synthetic aperture radar interferometry (PoIInSAR) processing, it is necessary to coregister all the images, including the coregistration of polarimetric SAR images and the coregistration of interferometric SAR images. Otherwise, the performance of the estimated optimal interferograms will be deteriorated. A generalized scattering vector (GSV) model is proposed to execute the PoIInSAR optimal interferograms estimation. The generalized scattering vector is constructed by the Pauli scattering vectors of the processing pixel and the surrounding pixels. Even though there are coregistration errors, all the polarimetric information of the current processing pixel is entirely included in the generalized scattering vector. Therefore, the GSV-based method can automatically recover the optimal scattering mechanisms of the processing pixel with coregistration errors either in interferoemetric channels or polarimetric channels. Theoretical analysis and processing results of simulated PoISARPro data and real PALSAR data validate the effectiveness and correctness of the proposed method.

关键词： polarimetric synthetic aperture radar interferometry (PoIInSAR) generalized scattering vector (GSV) optimal interferogram coregistration error Pauli basis

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Small universal simple spiking neural P systems with weights

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Science China(Information Sciences) 2014年第9期57卷 19-29页

作者： ZENG XiangXiang PAN LinQiang PREZ-JIMNEZ Mario J. Key Laboratory of Image Processing and Intelligent Control School of AutomationHuazhong University of Science and Technology Department of Computer Science and Artificial Intelligence University of SevillaAvda. Reina Mercedes s/nSevilla 41012Spain

Spiking neural P systems with weights(WSN P systems,for short)are a new variant of spiking neural P systems,where the rules of a neuron are enabled when the potential of that neuron equals a given *** is known that WSN P systems are universal by simulating register ***,in these universal systems,no bound is considered on the number of neurons and *** this work,a restricted variant of WSN P systems is considered,called simple WSN P systems,where each neuron has only one *** complexity parameter,the number of neurons,to construct a universal simple WSN P system is *** is proved that there is a universal simple WSN P system with 48 neurons for computing functions;as generator of sets of numbers,there is an almost simple(that is,each neuron has only one rule except that one neuron has two rules)and universal WSN P system with 45 neurons.

关键词： bio-inspired computing membrane computing P system spiking neural P system universal computing device

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Stability and Robust Stability of Stochastic Reaction-Diffusion Neural Networks With Infinite Discrete and Distributed Delays

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2020年第5期50卷 1721-1732页

作者： Sheng, Yin Zhang, Hao Zeng, Zhigang Huazhong Univ Sci & Technol Sch Automat Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Natl Lab Optoelect Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Hubei Peoples R China

This paper investigates the $\phi $ -type stability and robust stability for a general class of stochastic reaction-diffusion neural networks (SRDNNs) with Dirichlet boundary conditions, infinite discrete time-varying delays, and infinite continuously distributed delays. By virtue of inequality techniques, properties of $\boldsymbol M$ -matrix, and theories of stochastic analysis, several sufficient criteria are obtained to guarantee the almost sure $\boldsymbol \phi $ -type stability, $\boldsymbol p$ th moment $\boldsymbol \phi $ -type stability, and $\boldsymbol \phi $ -type robust stability of the underlying SRDNNs with hybrid unbounded time delays. With appropriate choices of the function $\boldsymbol \phi $ , the $\boldsymbol \phi $ -type stability reduces to the exponential stability, polynomial stability, and logarithmic stability. Additionally, the developed results herein include some existing ones as special cases. A numerical simulation is performed to substantiate the effectiveness and superiority of the theoretical analysis.

关键词： Infinite discrete delay infinite distributed delay robust stability stability stochastic reaction-diffusion neural networks (SRDNNs)

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Discrete-Time Positive Edge-Consensus for Undirected and Directed Nodal Networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2018年第2期65卷 221-225页

作者： Wu, Han Su, Housheng Huazhong Univ Sci & Technol Sch Automat Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan 430074 Hubei Peoples R China

This brief addresses the positive consensus of the edges with multi-input and multi-output positive dynamics for undirected and directed networks. The line graph is derived from the given nodal graph to represent the interaction of the edges, and the discrete-time positive systems are introduced to describe the edge dynamics. Based on the positive system theory and consensus analysis, a necessary and sufficient condition for positive edge-consensus is established, which reveals how the edge dynamics and the eigenvalues of the Perron matrix of line graph affect the consensus. Moreover, with further analysis, sufficient conditions for positive edge-consensus are derived without using the global interaction topology. It shows that the positive consensus can be achieved with the combined effect of edge dynamics, the number of edges, and the minimum diagonal element of the Perron matrix of line graph. The feedback matrix can be computed by solving linear programming problem. Finally, the simulations explicitly verify the proposed theoretical results.

关键词： Discrete-time positive edge-consensus MIMO line graph linear programming

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Consensus in Fractional-Order Multi-Agent Systems With Intermittence Sampled Data Over Directed Networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2020年第2期67卷 365-369页

作者： Ye, Yanyan Su, Housheng Chen, Jinhe Peng, Yaxin Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Min Wuhan 430074 Peoples R China

The leaderless consensus of fractional-order multi-agent systems (FOMASs) by intermittence sampled data control method is investigated in this brief, for which a distributed intermittence sampled data control protocol is presented to reduce the updating rate and working time of controllers. Subsequently, the Laplace transform and the stability theory are utilized to derive some necessary and sufficient consensus criteria that show the relations among the fractional order, sampling period, communication width, coupling strengths, and network topology. What is more, it can be discovered that both the communication width and sampling period have the lower and upper bounds for given networks to attain leaderless consensus. Finally, a numerical simulation example is presented to prove the theoretical results.

关键词： Laplace equations Protocols Multi-agent systems Distributed databases Couplings Kinetic theory Circuits and systems Fractional-order multi-agent system consensus sampled data communication width

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Spiking neural P systems with astrocytes using the rules in the exhaustive mode

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8961卷 274-283页

作者： Kong, Yuan Zhao, Dongming Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China School of Automation Wuhan University of Technology WuhanHubei430070 China

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired by the way neurons communicate by means of electrical impulses or spikes. SN P systems with astrocytes are a new variant of SN P systems, where astrocytes are introduced to control the amount of spikes passing along synapses. In this work, we investigate the computation power of SN P systems with astrocytes with the rules in any neuron used in the exhaustive manner, that is, the enabled rule in any neuron should be used as many times as possible at any moment. Specifically, it is obtained that such SN P systems can compute/generate any set of Turing computable natural numbers. © Springer International Publishing Switzerland 2014.

关键词： Neurons

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