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Carboxyl graphene oxide/graphene composite structure for the chemiresistive detection of acetaldehyde at room temperature

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SENSORS AND ACTUATORS B-CHEMICAL 2025年 427卷

作者： Li, Quanfu Feng, Fan Jiang, Chunsheng Song, Shuxiang Peng, Huiling Liao, Zhixian Guangxi Normal Univ Sch Elect & Informat Engn Guangxi Key Lab Brain Inspired Comp & Intelligent Guilin 541004 Peoples R China Guangxi Normal Univ Educ Dept Guangxi Zhuang Autonomous Reg Key Lab Integrated Circuits & Microsyst Guilin 541004 Peoples R China Guilin Univ Elect Technol Sch Elect Engn & Automat Guilin 541004 Peoples R China

The work systematically investigates the sensing performance of the carboxyl graphene oxide/graphene sensor (GO-COOH/Graphene) for acetaldehyde (CH3CHO). Firstly, carboxylated graphene oxide was prepared by employing sodium hydroxide and chloroacetic acid to convert epoxy and hydroxyl groups into carboxyl functional groups. Subsequently, the GO-COOH solution was uniformly deposited on the graphene film to fabricate the GO-COOH/Graphene sensor. Under the test conditions of 100 ppm CH3CHO, the response of the GO-COOH/ Graphene sensor was 86.29 times that of graphene and 5.44 times that of GO-COOH, with a response of 177.76 %, response time of 23 seconds, recovery time of 296 seconds, and theoretical limit of detection (LOD) is 42.3 ppb, indicating that the GO-COOH/Graphene sensor exhibits a rapid and highly sensitive response to CH3CHO at room temperature and high humidity. Additionally, the GO-COOH/Graphene sensor demonstrates outstanding selectivity, repeatability, and long-term stability in CH3CHO sensing. By capitalizing on the abundant functional groups of GO-COOH and the excellent electrical conductivity of graphene, the GO-COOH/ Graphene sensor effectively resolves the issues of poor response, slow response, and slow desorption of graphene in CH3CHO sensing. The composite structure proposed in this work holds significant application potential in domains such as human respiratory detection and environmental monitoring of CH3CHO.

关键词： Acetaldehyde Carboxyl graphene oxide Graphene gas sensor Composite structure

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Combine multi-order representation learning and frame optimization learning for skeleton-based action recognition

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DIGITAL SIGNAL PROCESSING 2025年 156卷

作者： Nong, Liping Huang, Zhuocheng Wang, Junyi Rong, Yanpeng Peng, Jie Huang, Yiping Guilin Univ Elect Technol Sch Informat & Commun Guilin 541004 Peoples R China Guangxi Normal Univ Sch Elect & Informat Engn Guangxi Key Lab Brain inspired Comp & Intelligent Guilin 541004 Peoples R China Guilin Univ Elect Technol Key Lab Cognit Radio & Informat Proc Minist Educ Guilin 541004 Peoples R China Guangxi Normal Univ Educ Dept Guangxi Zhuang Autonomous Reg Key Lab Integrated Circuits & Microsyst Guilin 541004 Peoples R China Guangxi Normal Univ Coll Phys & Technol Guilin 541004 Peoples R China

Skeleton-based action recognition has broad application prospects in many fields such as virtual reality. Currently, the most popular way is to employ Graph Convolutional Networks (GCNs) or Hypergraph Convolutional Networks (HGCNs) for this task. However, GCN-based methods may heavily rely on the physical connectivity relationship between joints while lack the capture of higher-order information about interactions among distant joints, and HGCN-based methods usually introduce unnecessary noise when capturing low-order information of skeleton structures with simple topology. Besides, the current methods do not deal well with redundant frames and confusing frames. These limitations hinder the improvement of recognition accuracy. In this paper, we propose a novel network, called Hyper-Net, which combines multi-order representation learning and frame optimization learning for skeleton-based action recognition. Specifically, the proposed Hyper-Net contains Temporal-Channel Aggregation Graph Convolution (TCA-GC), Spatial-Temporal Aggregation Hypergraph Convolution (STA-HC) and Frame Optimization Learning (F-OL) modules. The TCA-GC aggregates low-order and local information from simple joint and bone topologies across different temporal and channel dimensions. The STA-HC captures high- order and global information from complex motion streams as well as solving the problem of spatial-temporal weight imbalance. The F-OL can adaptively extract key frames and distinguish confusing frames, thus improving the ability of the network to recognize confusing actions. A large number of experiments are conducted on the NTU RGB+D, NTU RGB+D 120 and NW-UCLA datasets for action recognition task. Experimental results demonstrate the superiority and effectiveness of the proposed network.

关键词： Skeleton-based action recognition Graph convolutional network Hypergraph convolutional network Frame optimization learning

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Filippov FitzHugh-Nagumo Neuron Model with Membrane Potential Threshold Control Policy

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NEURAL PROCESSING LETTERS 2021年第5期53卷 3801-3824页

作者： Dong, Tao Zhu, Huiyun Southwest Univ Coll Elect & Informat Engn Key Lab Nonlinear Circuits & Intelligent Informat Chongqing 400715 Peoples R China

In this paper, a novel FitzHugh-Nagumo (FHN) neuron model with membrane potential threshold control policy is proposed. As the membrane potential threshold control policy is a switching control policy, our proposed model is a Filippov system, which is different from the existing FHN model. For this model, first, the sliding segments and sliding regions are investigated. Then, based on the obtained sliding regions, we discuss the null-clines and the existence conditions of various equilibria such as regular equilibrium, virtual equilibrium and boundary equilibrium. By choosing the membrane potential threshold as the bifurcation parameter, the boundary node bifurcation, pseudo-saddle-node bifurcation and the global touching bifurcation are investigated by using numerical techniques. Furthermore, the effectiveness and correctness of the proposed FHN model with membrane potential threshold control policy are verified by circuit simulation. Numerical examples show that the membrane potential threshold guided switching may cause complex dynamics.

关键词： Filippov system FitzHugh-Nagumo (FHN) neuron model Membrane potential threshold control policy Sliding bifurcation

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Dynamics of a Hybrid Circuit System With Lossless Transmission Line

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IEEE ACCESS 2020年 8卷 92969-92976页

作者： Dong, Tao Zhang, Qinqin Southwest Univ Key Lab Nonlinear Circuits & Intelligent Informat Coll Elect & Informat Engn Chongqing 400715 Peoples R China

In this paper, a hybrid circuit system composed of a Chua & x2019;s circuit with lossless transmission line and a oscillating circuit is considered. First, the equations describing the hybrid circuit system are reduced to a set of hybrid equations made up of a delayed neutral-type differential equation and a differential equation. By constructing the appropriate Lyapunov function, a novel condition of global stability is derived, which depends on the lower bound of . Using the length of transmission line as the bifurcation parameter, the conditions of local stability and Hopf bifurcation are obtained. Finally, the realization of our proposed circuit is given and two examples are given to verify the obtained theoretical analysis by using Matlab and Multisim14.0.

关键词： Power transmission lines Propagation losses Stability analysis Circuit stability Power system stability Bifurcation Mathematical model Lossless transmission line hybrid circuit system Hopf bifurcation differential equation stability

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A Class of nonlinear Kalman Filters Under a Generalized Measurement Model With False Data Injection Attacks

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IEEE SIGNAL PROCESSING LETTERS 2022年 29卷 1187-1191页

作者： Chen, Shanmou Zhang, Qiangqiang Lin, Dongyuan Wang, Shiyuan Southwest Univ Coll Elect & Informat Engn Key Lab Nonlinear Circuits & Intelligent Informat Chongqing 400715 Peoples R China

In this letter, a generalized measurement model (GMM) is established under the attack injecting additive and multiplicative false data, simultaneously. The GMM can be applied to any existing nonlinear Kalman filters (NKFs), such as extended Kalman filter (EKF), cubature Kalman filter (CKF), and geometric unscented Kalman filter (GUF). Based on the constructed GMM, a class of nonlinear Kalman filters with GMM (NKFs-GMM) is proposed to deal with additive false data, multiplicative false data, and simultaneous attacks on additive and multiplicative false data with no increase of computational complexity. Numerical simulations show that the filtering accuracy of NKFs-GMM is superior to that of corresponding NKFs.

关键词： Additives Kalman filters Data models Noise measurement Time measurement Numerical models Loss measurement Cyber attack false data generalized measurement model nonlinear Kalman filtering

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Adaptive Fixed-Time Control for Full State-Constrained nonlinear Systems: Switched-Self-Triggered Case

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IEEE TRANSACTIONS ON circuits AND SYSTEMS II-EXPRESS BRIEFS 2024年第2期71卷 752-756页

作者： Wang, Ziming Wang, Xin Pang, Ning Southwest Univ Coll Westa Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

In this brief, an one-to-one asymmetric NM based auxiliary system is put forward to deal with the state transformation problem for nonstrict full state-constrained systems under the adaptive fixed-time control. Then one proposed a novel switched-self-triggered mechanism (SSTM) in the controller update, which is helpful to obtain a better system performance. In addition, one can show that under the condition of state-constraints, semiglobal practical fixed-time stability (SPFTS) standard can also preserved both the tracking performance and the stability of the closed-loop system in a specified time. Finally, the effectiveness of the controller design is thoroughly shown via an illustrative simulation example.

关键词： Control systems Switches nonlinear systems Lyapunov methods Convergence Stability criteria nonlinear circuits Fixed-time control full-state constraints RBF NN switched-self-triggered mechanism (SSTM)

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A continuous-time neurodynamic algorithm for distributed nonconvex nonsmooth optimization problems with affine equality and nonsmooth convex inequality constraints

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NEUROCOMPUTING 2022年 507卷 383-396页

作者： Yang, Jianyu He, Xing Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

In this paper, a distributed nonsmooth nonconvex optimization (DNNO) problem with affine inequality and nonsmooth convex inequality constraints is studied. A continuous-time distributed neurodynamic algorithm is proposed to solve this problem. Under the assumed conditions, for any initial state, the solution of distributed neurodynamic algorithm is bounded and globally exists, and will converge to the critical point set of distributed problems in a finite time. Compared with other DNNO algorithms, distributed neurodynamic algorithm has a lower dimension and does not need to satisfy the assumption that the feasible region is bounded. Finally, a series of numerical examples are given to verify the effectiveness of the proposed *** 2022 Elsevier B.V. All rights reserved.

关键词： Continuous-time neurodynamic algorithm Distributed nonsmooth nonconvex optimization Finite-time convergence

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Edge-based distributed primal-dual algorithms for seeking generalized Nash equilibria

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EUROPEAN JOURNAL OF CONTROL 2024年 77卷

作者： Li, Huaqing Fan, Luming Ran, Liang Wang, Zheng Zheng, Zuqing Li, Zhe Li, Songyang Zheng, Lifeng Li, Jun Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

This paper introduces two novel distributed algorithms aimed at finding the generalized Nash equilibria (GNE) in noncooperative games. To tackle this, we utilize the variational inequality framework, transforming the noncooperative game into the challenge of identifying the zeros of a sum of monotone operators. Within noncooperative games, the decisions made by individual players are interlinked via shared affine constraints. Our proposed approach involves two edge -based distributed algorithms, differentiated by their access to players' actions, whether it is full -decision information or partial -decision information. We establish the parameter range and demonstrate the convergence of both algorithms, showcasing their efficacy under local constant step -sizes. Additionally, we validate the effectiveness and advantages of these algorithms through two numerical experiments.

关键词： Primal-dual method Distributed algorithm Non-cooperative game Generalized Nash equilibria (GNE)

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Stabilization of nonlinear delayed systems subject to impulsive disturbance via aperiodic intermittent control

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第6期361卷

作者： Wang, Yinuo Li, Chuandong Wu, Hongjuan Deng, Hao Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

In this paper, the finite -time stabilization (FS) of nonlinear delayed systems subject to impulsive disturbance is addressed via designing an aperiodic intermittent control (APIC), which can be segmented into time -triggered intermittent control (TAPIC) and event -triggered intermittent control (EAPIC). On account of Lyapunov method, sufficient conditions are exhibited to render FS can be achieved. Under TAPIC, the relationship between impulsive disturbance and control parameters is set up, from which the impulsive instants and the width of each control period can be resolved. In the framework of finite -time stabilization, the relationship among impulsive disturbance, intermittent control parameters, threshold value of event -triggered mechanism (ETM) under EAPIC is built up to ensure FS, and the sequence of impulsive disturbance instants is generated by the pre -designed ETM. Besides, the Zeno phenomenon can be ruled out. Based on the Chua's oscillator with time delay, two examples are depicted to demonstrate the validity of the acquired results under TAPIC and EAPIC, respectively.

关键词： Stabilization analysis nonlinear delayed systems Impulsive disturbance Aperiodic intermittent control Event-triggered control

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Recyclable solid waste detection based on image fusion and convolutional neural network

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JOURNAL OF MATERIAL CYCLES AND WASTE MANAGEMENT 2024年第4期26卷 2043-2057页

作者： Xiao, Yao Chen, Bin Feng, Changhao Qin, Jiongming Wang, Cong Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

The most solid waste image datasets usually contain only a single object with a plain background, which is quite different from the real environment. In addition, the waste images labeling process takes a long time and is labor cost. To address these problems, we proposed an effective method to extend the dataset based on image fusion. Herein, we use image fusion technology to make a recyclable solid waste dataset Trash-Fusion automatically, where the images contain different categories of objects with complex background, and all classification and location labels are collected in the process of image fusion. Moreover, an actual scene dataset Trash-Collect is constructed, images of which are downloaded from the Internet or collected by ourselves. A mixed dataset of Trash-Fusion and Trash-Collect is sent to several convolutional neural networks for training, and YOLO v5 achieves the highest detection precision with 60 FPS.

关键词： Recyclable solid waste Image fusion Convolutional neural network Mixed training Waste detection

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