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Distributed Constrained Optimization With Asynchrony and Delays

IEEE TRANSACTIONS ON circuits AND SYSTEMS II-EXPRESS BRIEFS 2022年第6期69卷 2772-2776页

作者： Su, Enbing Li, Huaqing Zheng, Zuqing Lu, Qingguo Wang, Zheng Xinzhou Teachers Univ Dept Comp Sci Xinzhou 034000 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

This brief investigates a distributed composite optimization problem over an undirected network with equality constraints. The optimization problem includes a smooth term and two possibly non-smooth terms. Most existing results are devoted to developing distributed algorithms in a synchronous setting with a global clock, where the agents cannot proceed to the next iteration until the slowest agent completes its update. A new asynchronous distributed primal-dual forward-backward splitting algorithm (AD-PDFBS) is presented to solve this problem. Each agent can compute and communicate independently at different times, for different durations, with the information it has even if the latest information from its neighbors is not yet available. The convergence of AD-PDFBS is proved by transforming the asynchronous algorithm into a fixed-point problem utilizing the operator splitting scheme under bounded delay assumption. Experiment result confirms the effectiveness of AD-PDFBS.

关键词： Optimization Convergence Delays Distributed algorithms Clocks Communication networks circuits and systems Asynchronous algorithm primal-dual algorithm forward-backward splitting method non-smooth function delay operator splitting scheme

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InspirationOnly: synthesizing expiratory CT from inspiratory CT to estimate parametric response map

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MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 2025年 1-18页

作者： Zhang, Tiande Pang, Haowen Wu, Yanan Xu, Jiaxuan Liang, Zhenyu Xia, Shuyue Jin, Chenwang Chen, Rongchang Qi, Shouliang Northeastern Univ Coll Med & Biol Informat Engn Shenyang Peoples R China Northeastern Univ Key Lab Intelligent Comp Med Image Minist Educ Shenyang Peoples R China Beijing Inst Technol Sch Integrated Circuits & Elect Beijing Peoples R China Guangzhou Med Univ Natl Ctr Resp Med Natl Clin Res Ctr Resp DisAffiliated Hosp 1 State Key Lab Resp DisGuangzhou Inst Resp Hlth Guangzhou Peoples R China Shenyang Med Coll Cent Hosp Resp Dept Shenyang Peoples R China Xi An Jiao Tong Univ Affiliated Hosp 1 Dept Radiol Xian Peoples R China South Univ Sci & Technol Affiliated Hosp 1 Shenzhen Peoples HospJinan Univ Shenzhen Inst Resp DisKey Lab Resp Dis ShenzhenA Shenzhen Peoples R China

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease with various phenotypes. Registered inspiratory and expiratory CT images can generate the parametric response map (PRM) that characterizes phenotypes' spatial distribution and proportions. However, increased radiation dosage, scan time, quality control, and patient cooperation requirements limit the utility of PRM. This study aims to synthesize a PRM using only inspiratory CT scans. First, a CycleGAN with perceptual loss and a multiscale discriminator (MPCycleGAN) is proposed and trained to synthesize registered expiratory CT images from inspiratory images. Next, a strategy named InspirationOnly is introduced, where synthesized images replace actual expiratory CT images. The image synthesizer outperformed state-of-the-art models, achieving a mean absolute error of 105.66 +/- 36.64 HU, a peak signal-to-noise ratio of 21.43 +/- 1.87 dB, and a structural similarity of 0.84 +/- 0.02. The intraclass correlation coefficients of emphysema, fSAD, and normal proportions between the InspirationOnly and ground truth were 0.995, 0.829, and 0.914, respectively. The proposed MPCycleGAN enables the InspirationOnly strategy to yield PRM using only inspiratory CT. The estimated COPD phenotypes are consistent with those from dual-phase CT and correlated with the spirometry parameters. This offers a potential tool for characterizing phenotypes of COPD, particularly when expiratory CT images are unavailable.

关键词： Deep learning Chronic obstructive pulmonary disease Generative adversarial network Artificial intelligence

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PEO-PDMS-based triboelectric nanogenerators as self-powered sensors for driver status monitoring

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CHEMICAL ENGINEERING JOURNAL 2023年第Part3期451卷

作者： Luo, Fangyuan Chen, Bin Ran, Xu Ouyang, Wei Shang, Liang Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuit & Intelligent Chongqing 400715 Peoples R China Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot & Intelligent Mfg Shenyang 110016 Peoples R China

The number of traffic accidents is growing with the ever-increasing vehicles, and most of the traffic accidents are due to fatigue or distracted driving. Thus, it is necessary to monitor the driver's status in real-time. However, current detection methods mainly rely on sensors that need a continuous power supply. Here, a polyethylene oxide (PEO)-polydimethylsiloxane (PDMS)-based triboelectric nanogenerator as a self-powered sensor was designed for biological signal monitoring. According to the experimental results, by adding green and low-cost substances sodium chloride and tea powder in PEO and PDMS films, respectively, the output voltage and current of the sensor are increased by about 9.75 and 8.21 times. The proposed sensor has a high sensitivity of 0.7 V/kPa in the linear range of 0-50 kPa and a fast response time of 36 ms. Moreover, a high-performance and low-cost driver status monitoring system was designed. The sensors were attached to the driver's neck and seat belt to monitor neck activities and breathing states. By extracting parameters from the output voltage waveform, the system can judge and display the degrees of driver fatigue and concentration. The proposed system is conducive to improving road traffic safety and has the potential to be applied in intelligent transportation.

关键词： PEO-PDMS-based triboelectric nanogenerator Self -powered sensor Respiratory signal detection Driver status monitoring

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Robustness comparison between the capsule network and the convolutional network for facial expression recognition

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APPLIED INTELLIGENCE 2021年第4期51卷 2269-2278页

作者： Li, Donghui Zhao, Xingcong Yuan, Guangjie Liu, Ying Liu, Guangyuan Southwest Univ Coll Elect & Informat Engn Chongqing Peoples R China Southwest Univ Inst Affect Comp & Informat Proc Chongqing Peoples R China Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing Peoples R China Southwest Univ Sch Math & Stat Chongqing Peoples R China

As an important part of human-computer interactions, facial expression recognition has become a popular research topic in computer vision, pattern recognition, artificial intelligence and other fields. With the development of deep learning and convolutional neural networks, research on facial expression recognition has also made considerable progress. Because facial expressions vary in real environments, such as rotation, shifting, brightness changes, partial occlusion and noise with different intensities, research on the robustness of facial expression recognition is very important. A capsule network consists of capsules, which are groups of neurons, and these capsules can learn posture information through the dynamic routing mechanism. The length of a capsule represents the existence probability, and each neuron in a capsule represents posture information (e.g., position, size, orientation or a combination of these properties). Therefore, in this study, the robustness of the emerging capsule network (CapsNet) is comprehensively compares with that of the traditional convolutional neural network (CNN) and fully convolutional network (FCN) in facial expression recognition tasks. The simulation results based on the Cohn-Kanade (CK+) databases show that the capsule network is more robust than the other networks. Therefore, the capsule network has significant advantages over the other networks in facial expression recognition task in complex real-world environments.

关键词： Facial expression recognition Robustness Capsule network Deep learning

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Wearable and self-powered triboelectric sensors based on NaCl/PVA hydrogel for driver multidimensional information monitoring

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NANO ENERGY 2023年第PartB期118卷

作者： Luo, Fangyuan Chen, Bin Ran, Xu Ouyang, Wei Yao, Youbin Shang, Liang Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuit & Intelligent Chongqing 400715 Peoples R China Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot & Intelligent Mfg Shenyang 110016 Peoples R China

Dangerous behaviors during driving such as fatigue or making phone calls may seem common in daily life. However, these behaviors are the actual "culprit" of many traffic accidents and pose a serious threat to traffic safety. Therefore, it is necessary to effectively detect dangerous driving behaviors by scientific and technological means. The present detection methods still face many bottlenecks, including individual differences, complex lighting changes, battery power supply, poor wearability, et al. Here, we designed a green and stretchable triboelectric sensor (TES) to monitor dangerous driving behaviors. The performance of the sensor was improved by about 9.99 and 3.58 times through doping sodium chloride solution in PVA hydrogel and introducing a curved contact surface between the electrode and friction layer, respectively. The proposed sensor has a high sensitivity of 1.95 V/kPa in the linear range of 0-11.28 kPa. By employing different machine learning models, we developed an intelligent neck ring based on the proposed sensor array to recognize different neck movements, which has achieved the highest accuracy of 96.10%. Finally, the intelligent neck ring was used to construct a sensing system for driver status monitoring. By collecting detailed driver information, the system can detect dangerous driving behaviors, monitor drivers' health conditions, and provide appropriate reminders to improve driving safety and prevent the spread of viruses.

关键词： NaCl/PVA hydrogel electrode Self-powered triboelectric sensor intelligent neck ring Machine learning Driver multidimensional information monitoring

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A memristor-based dual-domain system for overcoming limitations of traditional analogue compute-in-memory

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SCIENCE CHINA-MATERIALS 2025年

作者： Liu, Shixiong Sun, Tao Li, Yang Univ Jinan Sch Informat Sci & Engn Shandong Prov Key Lab Network Based Intelligent Co Jinan 250022 Peoples R China Shandong Univ Sch Integrated Circuits Jinan 250101 Peoples R China Shandong Univ Acad Intelligent Innovat Jinan 250101 Peoples R China

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Autonomic nervous pattern analysis of trait anxiety

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2022年第PartA期71卷 103129-103129页

作者： Kong, Fanmeng Wen, Wanhui Liu, Guangyuan Xiong, Ronglong Yang, Xuehong Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China

High trait anxiety (HTA) causes cognitive control deficit, implicit emotion regulation deficit and risks of emotional disorders. The current work designed a paradigm for autonomic nervous pattern analysis of trait anxiety. The paradigm includes three phases: (1) physiological data acquisition of autonomic nervous activity in resting baseline status, during the preparation and presentation of an evaluated speech, and in recovery status after stressful task;(2) feature extraction and selection of the physiological data;(3) pattern recognition of high/ low trait anxiety through commonly used classifiers. By the operation of the above paradigm, we analyzed 99 samples of respiratory (Resp) data and RR interval series calculated from the ECG data of 99 subjects. We have found that: (1) the autonomic nervous activity of trait anxiety has obvious gender difference;(2) After eliminating gender difference by modeling of trait anxiety for each gender, the HTA and low trait anxiety (LTA) populations can be distinguished by the decision tree classifier with accuracies of 66.67% and 100% for females and males, respectively;(3) for the females, the critical two-dimension feature subset of HTA vs. LTA classification comes from the resting baseline status, stress recall status and stress withdrawal status;(4) for the males, the critical two-dimension feature subset of HTA vs. LTA classification comes from the resting baseline status and the stress withdrawal status. The results have shown that HTA and LTA have baseline autonomic nervous difference, and the stress reactions of autonomic nervous system of HTA and LTA populations are different for different genders.

关键词： High trait anxiety Stressful task Heart rate variability Autonomic nervous system activity

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Exponential stability of discrete-time delayed neural networks with saturated impulsive control

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IET CONTROL THEORY AND APPLICATIONS 2021年第12期15卷 1628-1645页

作者： He, Zhilong Li, Chuandong Cao, Zhengran Li, Hongfei Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Xinjiang Univ Finance & Econ Sch Finance Urumqi Peoples R China Peking Univ Coll Engn Dept Mech & Engn Sci BIC ESATState Key Lab Turbulence & Complex Syst Beijing Peoples R China

This paper examines the problem of the locally exponentially stability for impulsive discrete-time delayed neural networks (IDDNNs) with actuator saturation. By fully considering the delay information of the state of the considered system, a new delay-dependent polytopic representation within a discrete-time framework is obtained. Based on the delay-independent polytopic representation approach, the saturation term is expressed as a delay-dependent convex combination. In order to obtain some less conservative stability conditions and estimate a larger of the domain of attraction, a novel type of Lyapunov-Krasovskii function (LKF) dependent on the delay information and the impulses instant is proposed, which is called time-dependent LKF. Then, by combining with the proposed LKF, a discrete Wirtinger-based inequality, an extended reciprocally convex matrix inequality and some novel analysis techniques, several new exponential stability criteria dependent on the bounds of the delay are presented. Moreover, when saturation constraints are not considered in the impulsive controller, the stability of the system is also discussed. Finally, two examples are given to confirm the applicability of the proposed results.

关键词： Neural nets (theory) Algebra Linear control systems Stability in control theory Discrete control systems Time-varying control systems Distributed parameter control systems

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Stability of nonlinear distributed delay system with parameter uncertainties: Integral-based event-triggered impulsive control strategy

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INTERNATIONAL JOURNAL OF ROBUST AND nonlinear CONTROL 2021年第18期31卷 9055-9073页

作者： Li, Hongfei Zhang, Liruo Zhang, Xiaoyu Yu, Junzhi Peking Univ Coll Engn Dept Adv Mfg & Robot BIC ESATState Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China Univ Auckland Dept Elect & Comp Engn Auckland New Zealand Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing Peoples R China

This article investigates the stability of nonlinear uncertain distributed delay system via integral-based event-triggered impulsive control (IETIC) strategy. First, a IETIC mechanism is presented to reduce the redundant data transmission over the system, in which the integral-based event-triggered mechanism uses the integration of system states over a time period in the past. Second, a new lemma is proposed to eliminate the Zeno behavior of the established model through the IETIC mechanism. Third, a novel Lyapunov-Krasovskii functional (LKF) method related to probability density function is constructed to guarantee the stability of the established model based on LMI conditions, where a probability density function is introduced as a distributed delay kernel. Compared with existing methods, the constructed novel LKF method is less conservative or requiring less number of decision variables. Numerical examples are further provided to confirm the effectiveness and advantages of the proposed approach.

关键词： integral-based event-triggered impulsive scheme Lyapunov-Krasovskii functional (LKF) probability density function uncertain nonlinear system

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Periodicity and global exponential periodic synchronization of delayed neural networks with discontinuous activations and impulsive perturbations

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NEUROCOMPUTING 2021年 431卷 111-127页

作者： He, Zhilong Li, Chuandong Cao, Zhengran Li, Hongfei Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Xinjiang Univ Finance & Econ Sch Finance Urumqi 830012 Peoples R China Peking Univ Coll Engn Beijing 100871 Peoples R China

In this paper, periodic dynamics and periodic synchronization of a class of delayed neural networks with discontinuous neuron activations and impulsive perturbations are investigated. Firstly, based on Filippov's functional differential inclusion and impulsive differential inclusions theory, the existence of solutions of the considered neural network system is studied. Secondly, according to Krasnoselskii's fixed point theorem on cones of set-valued analysis, sufficient conditions are provided for the existence of at least one periodic solution and at least two periodic solutions for the neural network systems. Furthermore, we also use Kakutani's fixed point theorem to give sufficient criteria for the existence of at least one periodic solution of the neural network systems. These results shown that there are still one or more periodic solutions for the neural networks with discontinuous activations under the impulsive effects. Moreover, sufficient criteria are given to the exponential periodic synchronization under the switching state-feedback control strategy with or without delay. Finally, two numerical simulation examples are presented to verify the correctness and validity of our main conclusions. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Discontinuous neural networks Impulsive perturbations Periodic solution Differential inclusion State-feedback controller Periodic synchronization

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