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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2021年第6期32卷 2443-2457页

作者： Wu, Tingfang Pan, Linqiang Yu, Qiang Tan, Kay Chen Soochow Univ Prov Key Lab Comp Informat Proc Technol Suzhou 215006 Peoples R China Soochow Univ Sch Comp Sci & Technol Suzhou 215006 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Tianjin Univ Coll Intelligence & Comp Tianjin Key Lab Cognit Comp & Applicat Tianjin 300072 Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China

Spiking neural P (SN P) systems are a class of discrete neuron-inspired computation models, where information is encoded by the numbers of spikes in neurons and the timing of spikes. However, due to the discontinuous nature of the integrate-and-fire behavior of neurons and the symbolic representation of information, SN P systems are incompatible with the gradient descent-based training algorithms, such as the backpropagation algorithm, and lack the capability of processing the numerical representation of information. In this work, motivated by the numerical nature of numerical P (NP) systems in the area of membrane computing, a novel class of SN P systems is proposed, called numerical SN P (NSN P) systems. More precisely, information is encoded by the values of variables, and the integrate-and-fire way of neurons and the distribution of produced values are described by continuous production functions. The computation power of NSN P systems is investigated. We prove that NSN P is Turing universal as number generating devices, where the production functions in each neuron are linear functions, each involving at most one variable;as number accepting devices, NSN P systems are proved to be universal as well, even if each neuron contains only one production function. These results show that even if a single neuron is simple in the sense that it contains one or two production functions and the production functions in each neuron are linear functions with one variable, a network of simple neurons are still computationally powerful. With the powerful computation power and the characteristic of continuous production functions, developing learning algorithms for NSN P systems is potentially exploitable.

关键词： Neurons Biological neural networks Biological system modeling Computational modeling Biological information theory Production Biomembranes Bio-inspired computing membrane computing (MC) numerical P (NP) system spiking neural P (SN P) system universality

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Distributed control of heterogeneous multi-agent systems with unknown control directions via event/self-triggered communication

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JOURNAL OF THE FRANKLIN INSTITUTE 2020年第17期357卷 12163-12179页

作者： Lei, Yan Wang, Yan-Wu Yang, Wu Liu, Zhi-Wei Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan Peoples R China

This paper investigates the leader-following output consensus of heterogeneous multi-agent systems (MASs) with unknown and nonidentical control directions under switching topology. To save the communication resources, a distributed adaptive control protocol together with an event-triggered communication scheme is proposed to achieve the output consensus. A self-triggered communication strategy is further given to prevent the continuous monitoring of neighbors states. Moreover, we prove that the proposed event/self-triggered strategies are Zeno-free. The obtained results are successfully applied to design the output formation controller. Finally, the effectiveness of the proposed theoretical results is demonstrated by two numerical examples. (C) 2020 Published by Elsevier Ltd on behalf of The Franklin Institute.

关键词： Multi agent systems

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Second-Order Consensus for Multiagent Systems via Intermittent Sampled Position Data control

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IEEE TRANSACTIONS ON CYBERNETICS 2020年第5期50卷 2063-2072页

作者： Su, Housheng Liu, Yifan Zeng, Zhigang Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

In this paper, a second-order consensus for multiagent systems with a directed communication topology is studied. A novel consensus strategy is first proposed, where a periodic intermittent control strategy only with casual sampled position data is used, which not only decreases the operating time and the update rates of conditioners for every individual but also responds effectively to the case of missing velocity information. A necessary and sufficient consensus condition based on the coupling gains, the sampling period, the communication width, and the spectrum of the Laplacian matrix is established to reach the consensus, and the right intervals of the sampling period are given. Furthermore, a delay-induced consensus protocol is designed, and a necessary and sufficient condition is also given, by which the sampling period and the communication width can easily be chosen to achieve the consensus. At last, some simulation examples are given to verify the correctness of the theoretical results.

关键词： Multi-agent systems Protocols Topology Eigenvalues and eigenfunctions Laplace equations Delay effects Couplings Communication width intermittent sampled position data multiagent system sampling period second-order consensus

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Observability of Heterogeneous Multi-Agent Systems

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2021年第2期8卷 1828-1841页

作者： Liu, Bo Shen, Xixi Wu, Licheng Su, Housheng Minzu Univ China Sch Informat Engn Beijing 100081 Peoples R China North China Univ Technol Coll Sci Beijing 100144 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

This paper investigates the observability of discrete-time heterogeneous multi-agent systems (MASs) under an absolute protocol with switching topology and fixed topology, respectively, in which the agents are first-order and second-order integrator agents. By properly decomposing the adjacency matrix of such system into sub-matrices and selecting an appropriate output vector measured by the leaders, the dynamics of the heterogeneous MASs can be modelled as a classical LTI system. Based on switched theory, some algebraic features on the observability of discrete-time heterogeneous MASs are obtained by taking advantage of the invariant subspace for switching topology. Specially, an unobservable subspace is established by designing a switching sequence. Moreover, some necessary and/ or sufficient conditions for the observability of heterogeneous MASs with fixed topology are also derived by using Popov-Belevitch-Hautus (PBH) and the observable rank criteria based on the partitioned sub-matrices. Finally, numerical examples and simulations are given to show the theoretical results.

关键词： Observability Topology controllability Protocols Switches Network topology Linear systems Observability heterogeneous MASs switching topology invariant subspace

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Trajectory-based operation monitoring of transition procedure in multimode process

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JOURNAL OF PROCESS control 2020年 96卷 67-81页

作者： Wang, Zhaojing Zheng, Ying Wong, David Shan-Hill Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Natl Tsing Hua Univ Dept Chem Engn Hsinchu Taiwan

Many continuous industrial processes operate in different steady states with different grades or products. The switching between two steady states is called transition. Transition consists of a series of operation changes that should be carried out in proper order, within certain magnitudes and time region. Since faulty operation may lead to increase in inferior products or even hazard events, monitoring of the transition is desired. In this work, a transition identification and monitoring scheme is proposed based on slow feature analysis. Two monitoring statistics which represent the location of the trajectory and the speed of transition are proposed. Besides, operating faults are generated based on the guidewords of hazard and operability analysis (HAZOP). Using a numerical case and the mode 4-to-2 transition of the Tennessee-Eastman process in which catastrophic failures exist, the effectiveness of the proposed method is validated. In addition to missed detection rate and false alarm rate, two performance indexes known as detection time (DT) and rescue time (RT) are introduced. The advantages of proposed method are benchmarked against the stage-based sub principle component analysis(sub-PCA) and the global preserving statistics slow feature analysis(GSSFA). (C) 2020 Published by Elsevier Ltd.

关键词： Transition monitoring Operating faults Transition identification Trajectory-based method

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Exponential Stabilization of Inertial Memristive Neural Networks With Multiple Time Delays

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IEEE TRANSACTIONS ON CYBERNETICS 2021年第2期51卷 579-588页

作者： Sheng, Yin Huang, Tingwen Zeng, Zhigang Li, Peng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Texas A&M Univ Qatar Sci Program Doha Qatar Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

This article investigates the global exponential stabilization (GES) of inertial memristive neural networks with discrete and distributed time-varying delays (DIMNNs). By introducing the inertial term into memristive neural networks (MNNs), DIMNNs are formulated as the second-order differential equations with discontinuous right-hand sides. Via a variable transformation, the initial DIMNNs are rewritten as the first-order differential equations. By exploiting the theories of differential inclusion, inequality techniques, and the comparison strategy, the pth moment GES (p >= 1) of the addressed DIMNNs is presented in terms of algebraic inequalities within the sense of Filippov, which enriches and extends some published results. In addition, the global exponential stability of MNNs is also performed in the form of an M-matrix, which contains some existing ones as special cases. Finally, two simulations are carried out to validate the correctness of the theories, and an application is developed in pseudorandom number generation.

关键词： Comparison approach exponential stability exponential stabilization inertial memristive neural networks (IMNNs) time delays

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DeepTI: A deep learning-based framework decoding tumor-immune interactions for precision immunotherapy in oncology

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SLAS DISCOVERY 2022年第2期27卷 121-127页

作者： Ma, Jianfei Jin, Yan Tang, Yuanyuan Li, Lijun Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Luoyu Rd 1037 Wuhan 430074 Peoples R China Xinxiang Med Univ Sch Basic Med Sci Dept Human Anat & Histoembryol Xinxiang 453003 Henan Peoples R China Zhengzhou Univ State Key Lab Esophageal Canc Prevent & Treatment Zhengzhou 450052 Henan Peoples R China Zhengzhou Univ Henan Key Lab Esophageal Canc Res Affiliated Hosp 1 Zhengzhou 450052 Henan Peoples R China Key Lab Mol Neurol Xinxiang Xinxiang 453003 Henan Peoples R China Zhejiang Univ Sch Med Affiliated Hosp 2 Dept Orthoped Hangzhou 310000 Peoples R China Zhejiang Univ Orthoped Res Inst Hangzhou 310000 Peoples R China Key Lab Motor Syst Dis Res & Precis Therapy Zheji Hangzhou Zhejiang Peoples R China

Background: Increasing evidence suggests the immunomodulatory potential of genes in oncology. But the identification of immune attributes of genes is costly and time-consuming, which leads to an urgent demand to develop a prediction model. Method: We developed a deep learning-based model to predict the immune properties of genes. This model is trained in 70% of samples and evaluated in 30% of samples. Furthermore, it uncovers 60 new immune-related genes. We analyzed the expression perturbation and prognostic value of these genes in gastric cancer. Finally, we validated these genes in immunotherapy-related datasets to check the predictive potential of immunotherapeutic sensitivity. Result: This model classifies genes as immune-promoted or immune-inhibited based on the human PPI network and it achieves an accuracy of 0.68 on the test set. It uncovers 60 new immune-related genes, most of which are validated in the published literature. These genes are found to be downregulated in gastric cancer and significantly associated with the immune microenvironment in gastric cancer. Analysis of immunotherapy shows that these genes can discriminate between responder and non-responder. Conclusion: This model can facilitate the identification of immune properties of genes, decoding tumor-immune interactions for precision immunotherapy in oncology.

关键词： Immunotherapy Deep learning Oncology Precision medicine Immunity

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Between-class difference analysis based multidimensional RBC for multivariate fault isolation of industrial processes

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JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS 2020年 115卷 1-12页

作者： Zheng, Ying Liu, Lang Zhou, Wei Yang, Weidong Wong, David Shan-Hill Huazhong Univ Sci & Technol Key Lab Image Informat Proc & Intelligent Control Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Natl Tsing Hua Univ Dept Chem Engn Hsinchu Taiwan

In industrial process, fault isolation technology will identify the major variables leading to faults. The existing fault isolation methods usually have "smearing effect", cannot identify the sensitivity of the fault variables, or require too much calculation. To solve the above problems, a multivariate fault isolation method based on between-class difference analysis and multidimensional reconstruction-based contribution (RBC) is proposed in this work. First, two kind of strategies, i.e.,principle component analysis (PCA) and fisher discriminant analysis (FDA), are adopted to obtain the sensitivity indicators of the variables to the faults respectively, which is taken as the basis for determining the optimal reconstruction direction. Then, multidimensional RBC is used to determine the number of fault variables based on the selected reconstruction direction. Finally, the primary and secondary fault variables are isolated according to their fault sensitivities. The feasibility of the proposed method is illustrated by a numerical simulation example and TE process. To sum up, the proposed method provide sensitivity information of each fault variables and high diagnosis rate. Moreover, it also has an advantage in reducing the calculation time because of the preliminary selection of fault variables.(c) 2020 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Multivariate fault isolation Between-class differences analysis Principal component analysis Fisher discriminant analysis Multi-dimensional RBC

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Observability of Leader-Based Discrete-Time Multi-Agent Systems Over Signed Networks

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2021年第1期8卷 25-39页

作者： Liu, Bo Su, Housheng Wu, Licheng Shen, Xixi Minzu Univ China Sch Informat Engn Beijing 100081 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China North China Univ Techol Coll Sci Beijing 100144 Peoples R China

This paper models a class of leader-based discrete-time multi-agent systems (MASs) over signed networks with both positive edges and negative edges, and addresses the observability of such multi-agent network based on an agreement protocol. Some new algebraic and graphical characterisations of the observability are given using a signed Laplacian. In addition, for a structurally balanced network, the observability of a leader-follower discrete-time signed network with structurally balanced condition is equivalent to that of the corresponding unsigned network, if the leaders are selected from the same partitioned subset. Some numerical examples and simulations are given to demonstrate the analysis.

关键词： Observability Switches controllability Laplace equations Topology Nickel Network topology Multi-agent systems observability signed networks structural balance

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High Information Density and Low Coverage Data Storage in DNA with Efficient Channel Coding Schemes

arXiv

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arXiv 2024年

作者： Ding, Yi He, Xuan Nguyen, Tuan Thanh Song, Wentu Yakhini, Zohar Yaakobi, Eitan Pan, Linqiang Tang, Xiaohu Cai, Kui Information Coding and Transmission Key Lab of Sichuan Province Southwest Jiaotong University Sichuan Chengdu611756 China Cluster Singapore University of Technology and Design 487372 Singapore Faculty of Computer Science Technion - Israel Institute of Technology Haifa3200003 Israel School of Computer Science RUNI Herzliya4615200 Israel Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China

DNA-based data storage has been attracting significant attention due to its extremely high data storage density, low power consumption, and long duration compared to conventional data storage media. Despite the recent advancements in DNA data storage technology, significant challenges remain. In particular, various types of errors can occur during the processes of DNA synthesis, storage, and sequencing, including substitution errors, insertion errors, and deletion errors. Furthermore, the entire oligo may be lost. In this work, we report a DNA-based data storage architecture that incorporates efficient channel coding schemes, including different types of error-correcting codes (ECCs) and constrained codes, for both the inner coding and outer coding for the DNA data storage channel. We also carried out large scale experiments to validate our proposed DNA-based data storage architecture. Specifically, 1.61 and 1.69 MB data were encoded into 30,000 oligos each, with information densities of 1.731 and 1.815, respectively. It has been found that the stored information can be fully recovered without any error at average coverages of 4.5 and 6.0, respectively. This experiment achieved the highest net information density and lowest coverage among existing DNA-based data storage experiments (with standard DNA), with data recovery rates and coverage approaching theoretical optima. Copyright © 2024, The Authors. All rights reserved.

关键词： Channel coding

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