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Stability of Boolean networks with state-dependent random impulses

Ya-wen Shen, Yu-qian Guo, Wei-hua Gui,shenyawen@csu.edu.cn,gyuqian@csu.edu.cn,gwh@csu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 2,   Pages 141-286 doi: 10.1631/FITEE.1900454

Abstract: We investigate the stability of Boolean networks (BNs) with impulses triggered by both states and random

Keywords： Boolean network with impulses     Forward completeness     Finite-time stability with probability one     Asymptotical    

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Output feedback stabilizer design of Boolean networks based on network structure Research Articles

Jie ZHONG, Bo-wen LI, Yang LIU, Wei-hua GUI

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 247-259 doi: 10.1631/FITEE.1900229

Abstract: We present analytical investigations on output feedback stabilizer design of Boolean networks (BNs) toBased on network structure information describing coupling connections among nodes, an output feedbackFinally, a signal transduction network and a D. melanogaster segmentation polarity gene network are presented

Keywords： Boolean networks     Output feedback stabilizer     Network structure     Semi-tensor product of matrices    

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Optimal one-bit perturbation in Boolean networks based on cascading aggregation Research Articles

Jin-feng PAN, Min MENG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 294-303 doi: 10.1631/FITEE.1900411

Abstract: BOAs) of desired attractors and minimizes the size of the BOAs of undesired attractors for large-scale BooleanFinally, the efficiency of the proposed method is verified by a T-cell receptor network.

Keywords： Large-scale Boolean network     Attractor     Cascading aggregation     One-bit perturbation    

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Asurvey on complex dynamical networkswith impulsive effects Review Articles

Xiu-ping HAN, Yong-shun ZHAO, Xiao-di LI

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 199-219 doi: 10.1631/FITEE.1900456

Abstract: Five aspects of CDNs with impulsive effects are surveyed, including synchronizing impulses, desynchronizingimpulses, adaptive-impulsive synchronization, pinning impulsive synchronization, and CDNs with stochastic

Keywords： Complex dynamical networks     Synchronizing impulses     Desynchronizing impulses     Pinning control     Time delay    

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Complete synchronization of coupled Boolean networks with arbitrary finite delays Research Articles

Jie LIU, Lulu LI, HabibM. FARDOUN

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 281-293 doi: 10.1631/FITEE.1900438

Abstract: In this study, the complete synchronization problem of coupled delayed Boolean networks (CDBNs) is investigatedThe state delays and output delays may not be equal, and the state delay in each Boolean network may

Keywords： Boolean networks     Synchronization     Time delay    

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Cascading decomposition of Boolean control networks: a graph-theoreticalmethod Research Articles

Yi-feng LI, Jian-dong ZHU

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 304-315 doi: 10.1631/FITEE.1900422

Abstract: Two types of cascading decomposition problems of Boolean control networks are investigated using a raph-theoretical

Keywords： Boolean control networks     Semi-tensor product     Cascading decomposition     Graphic condition    

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Controllability of Boolean control networks with multiple time delays in both states and controls Research Article

Yifeng LI, Lan WANG,liyifeng@cqnu.edu.cn,wanglan202212@126.com

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 6,   Pages 906-915 doi: 10.1631/FITEE.2200618

Abstract: In this paper, the problem of of (BCNs) with multiple s in both states and controls is investigated. First, the problem of BCNs with multiple s in controls is considered. For this problem, a matrix is constructed by defining a new product of matrices, based on which a necessary and sufficient condition is obtained. Then, the of BCNs with multiple s in states is studied by giving a necessary and sufficient condition. Subsequently, based on these results, a matrix for BCNs with multiple s in both states and controls is proposed that provides a concise condition. Finally, two examples are given to illustrate the main results.

Keywords： Boolean control networks     Semi-tensor product of matrices     Controllability     Time delay    

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Bisimulation-based stabilization of probabilisticBoolean control networkswith state feedback control Research Articles

Nan JIANG, Chi HUANG, Yao CHEN, Jürgen KURTHS

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 268-290 doi: 10.1631/FITEE.1900447

Abstract: This study is concerned with probabilistic Boolean control networks (PBCNs) with state feedback controlThe results are then extended to the probabilistic Boolean networks.

Keywords： Probabilistic Boolean control network     Bisimulation     Stabilization with probability one     State feedback    

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An algorithm for identifying symmetric variables based on the order eigenvalue matrix Article

Xiao-hua LI, Ji-zhong SHEN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1644-1653 doi: 10.1631/FITEE.1601052

Abstract: To simplify the process for identifying 12 types of symmetric variables in Boolean functions, we propose12 types of symmetric variables, an algorithm is proposed for identifying symmetric variables of the BooleanThis algorithm can be applied to identify the symmetric variables of Boolean functions with or withoutis an optimal detection method in terms of the applicability of the number of logic variables, the Boolean

Keywords： Boolean function     Symmetric variable     Boolean logic algebra system     Order eigenvalue matrix     Truth table    

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Switching-based stabilization of aperiodic sampled-data Boolean control networks with all subsystems Research Articles

Liang-jie SUN, Jian-quan LU, Wai-Ki CHING

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 260-267 doi: 10.1631/FITEE.1900312

Abstract: We aim to further study the global stability of Boolean control networks (BCNs) under aperiodic sampleddataAccording to our previous work, it is known that a BCN under ASDC can be transformed into a switched Booleannetwork (SBN), and further global stability of the BCN under ASDC can be obtained by studying the global

Keywords： Aperiodic sampled-data control     Boolean control networks     Unstable subsystem     Discretized Lyapunov function    

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Novel interpretable mechanism of neural networks based on network decoupling method

Frontiers of Engineering Management 2021, Volume 8, Issue 4,   Pages 572-581 doi: 10.1007/s42524-021-0169-x

Abstract: The lack of interpretability of the neural network algorithm has become the bottleneck of its wide applicationdimension reduction method of high-dimensional system and reveal the calculation mechanism of the neural networkWe apply our framework to some network models and a real system of the whole neuron map of CaenorhabditisResult shows that a simple linear mapping relationship exists between network structure and network behaviorin the neural network with high-dimensional and nonlinear characteristics.

Keywords： neural networks     interpretability     dynamical behavior     network decouple    

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A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0736-9

Abstract: Recently, advanced sensing techniques ensure a large number of multivariate sensing data for intelligent fault diagnosis of machines. Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studied in the fault diagnosis field. However, existing studies suffer from two weaknesses. First, the relations of multiple sensors are either neglected or calculated only to improve the diagnostic accuracy of fault types. Second, the localization for multi-source faults is seldom investigated, although locating the anomaly variable over multivariate sensing data for certain types of faults is desirable. This article attempts to overcome the above weaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor relations (MSRs). First, an MSR model is developed to learn MSRs automatically and further obtain fault recognition results. Second, centrality measures are employed to analyze the MSR graphs learned by the MSR model, and fault sources are therefore determined. The proposed method is demonstrated by experiments on an induction motor and a centrifugal pump. Results show the proposed method’s validity in diagnosing fault types and sources.

Keywords： fault recognition     fault localization     multi-sensor relations     network analysis     graph neural network    

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Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 6,   Pages 1285-1298 doi: 10.1007/s11709-020-0691-7

Abstract: This article intends to model the multiscale constitution using feedforward neural network (FNN) andrecurrent neural network (RNN), and appropriate set of loading paths are selected to effectively predict

Keywords： multiscale method     constitutive model     feedforward neural network     recurrent neural network    

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Heat, mass, and work exchange networks

Zhiyou CHEN, Jingtao WANG

Frontiers of Chemical Science and Engineering 2012, Volume 6, Issue 4,   Pages 484-502 doi: 10.1007/s11705-012-1221-5

Abstract: This review presents the main works related to each network.

Keywords： process system engineering     integration methods     heat exchange network     mass exchange network     work exchangenetwork    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 814-828 doi: 10.1007/s11465-021-0650-6

Abstract: To address this issue, this paper explores a decision-tree-structured neural network, that is, the deepconvolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings.The proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision

Keywords： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network    

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Title Author Date Type Operation

Stability of Boolean networks with state-dependent random impulses

Ya-wen Shen, Yu-qian Guo, Wei-hua Gui,shenyawen@csu.edu.cn,gyuqian@csu.edu.cn,gwh@csu.edu.cn

Journal Article

Output feedback stabilizer design of Boolean networks based on network structure

Jie ZHONG, Bo-wen LI, Yang LIU, Wei-hua GUI

Journal Article

Optimal one-bit perturbation in Boolean networks based on cascading aggregation

Jin-feng PAN, Min MENG

Journal Article

Asurvey on complex dynamical networkswith impulsive effects

Xiu-ping HAN, Yong-shun ZHAO, Xiao-di LI

Journal Article

Complete synchronization of coupled Boolean networks with arbitrary finite delays

Jie LIU, Lulu LI, HabibM. FARDOUN

Journal Article

Cascading decomposition of Boolean control networks: a graph-theoreticalmethod

Yi-feng LI, Jian-dong ZHU

Journal Article

Controllability of Boolean control networks with multiple time delays in both states and controls

Yifeng LI, Lan WANG,liyifeng@cqnu.edu.cn,wanglan202212@126.com

Journal Article

Bisimulation-based stabilization of probabilisticBoolean control networkswith state feedback control

Nan JIANG, Chi HUANG, Yao CHEN, Jürgen KURTHS

Journal Article

An algorithm for identifying symmetric variables based on the order eigenvalue matrix

Xiao-hua LI, Ji-zhong SHEN

Journal Article

Switching-based stabilization of aperiodic sampled-data Boolean control networks with all subsystems

Liang-jie SUN, Jian-quan LU, Wai-Ki CHING

Journal Article

Novel interpretable mechanism of neural networks based on network decoupling method

Journal Article

A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Journal Article

Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Journal Article

Heat, mass, and work exchange networks

Zhiyou CHEN, Jingtao WANG

Journal Article

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Journal Article