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Chaotic dynamics, topological analysis and flat analog electronic control by physiological signals of a neurally-inspired system

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Chinese Journal of Physics 2025年 96卷 20-52页

作者： Tabekoueng Njitacke, Zeric Ngamsa Tegnitsap, Joakim Vianney Zhao, Manyu Barà, Chiara Fozin, Théophile Fonzin Awrejcewicz, Jan Yoshimura, Natsue Valdes-Sosa, Pedro A. Letellier, Christophe Minati, Ludovico School of Life Science and Technology University of Electronic Science and Technology of China Chengdu 611731 China Department of Electrical and Electronic Engineering College of Technology (COT) University of Buea P.O. Box 63 Buea Cameroon Fotso-Victor University Institute of Technology University of Dschang P.O. Box 134 Dschang Cameroon Research Unit of Condensed Matter Electronics and Signal Processing Department of Physics University of Dschang Cameroon Department of Engineering University of Palermo Palermo 90128 Italy Department of Electrical and Electronic Engineering Faculty of Engineering and Technology (FET) University of Buea P.O. Box 63 Buea Cameroon Department of Automation Biomechanics and Mechatronics Łódź University of Technology Stefanowskiego Str. 1/15 Lodz 90-924 Poland School of Computing Institute of Science Tokyo (formerly Tokyo Institute of Technology) Yokohama Japan ATR Brain Information Communication Research Laboratory Group Kyoto Japan Department of Neuroinformatics Cuban Neuroscience Center Havana 11600 Cuba CORIA Rouen Normandie University Saint-Etienne du Rouvray 76800 France Center for Mind/Brain Sciences (CIMeC) University of Trento Trento 38123 Italy

A novel abstract bicompartmental neural model based on a cubic nonlinearity, consisting of introducing a Josephson junction as a coupling element, is presented. Through numerical simulations and experimental measurements involving an analog electronic circuit, it is found that the system can generate a double-scroll chaotic attractor endowed with a remarkably complex topology. This is accompanied by diversification of the spectral signature across its four variables and multistability. An analysis of the global observability and controllability is conducted, leading to the synthesis of a flat controller that can steer the dynamics towards those of structurally different entities, as exemplified by a modified Lorenz system. The first analog realization of flat control is then introduced. The possibility of low-latency and high-accuracy manipulation of the dynamics is demonstrated by considering the challenging case of tracking extraneous external signals, namely, physiological recordings indexing autonomic and central nervous system activity. Besides showing the flexibility and adaptability of the approach, the controller enables the concomitant generation of multiple additional signals with spectrogram features compared to the individual inputs, offering a promising substrate for future applications in physical time series data augmentation. © 2025 The Physical Society of the Republic of China (Taiwan)

关键词： Chaotic circuits Flat control Josephson junction Multistability Neural models Physiological recordings Topological analysis

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Vector Field-Guided Circumnavigation for an Unmanned Surface Vehicle With Boundary and Obstacle Constraints

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IEEE Transactions on Emerging Topics in Computing 2025年

作者： Wu, Nailong Wang, Jigang Wang, Yueying He, Shuping Donghua University College of Information Science and Technology Shanghai201620 China Donghua University Engineering Research Center of Digitized Textile & Apparel Technology Ministry of Education Shanghai201620 China Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Electrical Engineering and Automation Hefei230601 China

This article aims to tackle the challenge of rapid target circumnavigation by unmanned surface vehicles (USVs) under boundary and obstacle constraints through leveraging an emerging computing architecture specifically tailored for unmanned systems. Owing to the underactuation of USV dynamic systems and the presence of various time-varying surface disturbances, attaining rapid and accurate position control along with maneuverability poses a significant challenge to USVs. Therefore, when an USV maneuvers around a target in a confined search area with obstacles, it is essential for the guidance law to consider collision risks and environmental disturbances. This paper proposes a modified Lyapunov vector field with heading deviation compensation to circle the target in complex search regions. The vector field is designed to increase the radial velocity of the USV and accelerate convergence towards the target circle during the pursuit phase. By combining the proposed Lyapunov vector field with a boundary vector field, the USV can swiftly avoid boundaries and dynamic obstacles and then continue circling the target. The proposed computing architecture extends the application scope of the target circumnavigation to practical water surface environments, which is validated by extensive simulations and rigorous experiments. © 2025 IEEE.

关键词： Unmanned surface vehicles

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An interference suppression algorithm for cognitive bistatic airborne radars

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Journal of Systems Engineering and Electronics 2022年第3期33卷 585-593页

作者： XIA Deping ZHANG Liang WU Tao HU Wenjun National Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China Nanjing Research Institute of Electronics Technology Nanjing 210039China

Interference suppression is a challenge for radar researchers, especially when mainlobe and sidelobe interference coexist. We present a comprehensive anti-interference approach based on a cognitive bistatic airborne radar. The risk of interception is reduced by lowering the launch energy of the radar transmitting terminal in the direction of interference;main lobe and sidelobe interferences are suppressed via cooperation between the two radars. The interference received by a single radar is extracted from the overall radar signal using multiple signal classification(MUSIC), and the interference is cross-located using two different azimuthal angles. Neural networks allowing good, non-linear nonparametric approximations are used to predict the location of interference, and this information is then used to preset the transmitting notch antenna to reduce the likelihood of interception. To simultaneously suppress mainlobe and sidelobe interferences, a blocking matrix is used to mask mainlobe interference based on azimuthal information, and an adaptive process is used to suppress sidelobe interference. Mainlobe interference is eliminated using the data received by the two radars. Simulation verifies the performance of the model.

关键词： interference suppression cognitive bistatic airborne radar neural network blocking matrix

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A full-aperture imaging algorithm for hybrid sliding spotlight bistatic SAR

A full-aperture imaging algorithm for hybrid sliding spotlig...

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IET International radar Conference 2013

作者： Zhou, F. Sun, G.C. Xing, M.D. Yang, J. Science and Technology on Radar Signal Processing Laboratory Xidian University Xi'an China

ISBN: (纸本)9781849196031

A new full-aperture imaging algorithm for Spaceborne/ Airborne hybrid sliding spotlight bistatic SAR is proposed in this paper. The SAR configuration under discussion has great advantage over traditional ones, yet suffers from the double square-root term in the bistatic slant range equation and severe spatial variance. The proposed method firstly eliminates azimuth spectrum folding by the SPECAN operation, and then corrects the RCM by Chirp Scaling Algorithm. Without interpolation and sub-aperture operations, the algorithm is high in the computational efficiency and simple in the flow. Simulation results confirm the validity of the proposed algorithm.

关键词： Spectrum analysis

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A multi-frame track-before-detect algorithm based on root label clustering for multiple targets

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Chinese Journal of Aeronautics 2022年第5期35卷 87-96页

作者： Jiaqi ZHANG Haihong TAO Xiushe ZHANG Chunlei HAN State Key laboratory of Radar Signal Processing Xidian UniversityXi’an 710068China Xi’an Research Institute of Navigation Technology Xi’an 710071China

In this paper,a novel multi-frame track-before-detect algorithm is proposed,which is based on root label clustering to reduce the high computational complexity arising by observation area expansion and clutter/noise density increase.A criterion of track extrapolation is used to construct state transition set,root label is marked by state transition set to obtain the distribution information of multiple targets in measurement space,then measurement plots of multi-frame are divided into several clusters,and finally multi-frame track-before-detect algorithm is implemented in each *** computational complexity can be reduced by employing the proposed *** results show that the proposed algorithm can accurately detect multiple targets in close proximity and reduce the number of false tracks.

关键词： Multi-frame track-before-detect Multiple targets detection Root label clustering State transition set Track extrapolation

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Robust Optimization-based Neural Architectures Against Adversarial Attacks

Robust Optimization-based Neural Architectures Against Adver...

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IEEE SSD International Multi-Conference on Systems, signals and Devices

作者： Khaoula Ben Ali Seifeddine Messaoud Mohamed Ali Hajjaji Mohamed Atri Noureddine Liouane Laboratory of Automatic Signal Image Processing National Engineering School Monastir University Monastir Tunisia Faculty of Sciences of Monastir Monastir University Monastir Tunisia Higher Institute of Applied Sciences and Technology of Sousse Sousse University Sousse Tunisia Computer Engineering Department College of Computer Science King Khalid University Abha Saudi Arabia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Recent years have seen a rapid development in Machine Learning, which has profoundly influenced many areas of science and engineering. Among them, computer vision takes the leading place, where important tasks are image classifications powered by CNNs. Despite the great performance of CNNs in complicated scenarios, they remain sensitive to so-called adversarial attacks, and deliberate perturbations leading them to incorrect predictions. Besides more innocuous consequences, this has serious security implications for critical applications, in-cluding medical diagnostics, where misclassifications might result in disastrous outcomes. This research work discusses adversarial attacks on CNNs and other DNNs in computer vision, studying a full range of the generation and detection methods with details while discussing intrinsic vulnerability and robustness. It also proposes a learning framework that will enhance the robustness and security of DNNs and CNNs against such adversarial perils. The ultimate goal is directed to an improvement in the reliability of such models in absolutely critical scenarios for safe deployment into applications where accuracy is crucial.

关键词： Computer vision Accuracy Perturbation methods Computer network reliability Machine learning Robustness Security Medical diagnosis Resilience Image classification

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Modeling and analysis of connected elements interferometry error influencing factors

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Journal of Beijing Institute of technology 2016年第S2期25卷 166-169页

作者：赵培焱王斌王帆 National Key Laboratory of Science and Technology on Blind Signal Processing

Space security is facing unprecedented challenges with more and more crowded *** elements interferometry(CEI) is a new radio interference measurement technology,which can achieve high precision of angle measurement on a short baseline,it is expected to be independent or combined with other method to open up a new area of orbit ***,the influence of time delay measurement and baseline length on angle estimation are analyzed;secondly,the theoretical modeling of the propagation error is carried out,and then the influence of the ionosphere and troposphere are simulated and analyzed;finally,the error of the measurement equipment is modeled,then the clock synchronization error,frequency error and location error are analyzed *** results have important effects on the next research and engineering application of CEI.

关键词： space security connected elements interferometry(CEI) theoretical modeling accuracy analysis

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A space debris detection method based on distributed radar

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Journal of Beijing Institute of technology 2016年第S2期25卷 170-174页

作者：宋科康赵培焱王斌彭华峰 National Key Laboratory of Science and Technology on Blind Signal Processing

The radar echoes of space debris are weak and difficult to be *** at this problem,a distributed radar observation model is built combined with orbit characteristics of space debris,and a centralized CA-CFAR(constant false alarm rate) detection method with incoherent integration is proposed for space debris ***,the space debris scattering property and echoes model are ***,the multistation centralized cooperative detection system is applied,and as the space noise environment is well relatively,a CA-CFAR detector is adopted that follows the traditional incoherent integration,which solves the problem that echoes parameter can’t be estimated correctly and is propitious to space debris *** with four radars shows that the method can improve detection probability of space debris by 40% compared with one radar when the SNR is 10 dB.

关键词： centralized detection constant false alarm rate(CFAR) space debris distributed radar

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Unsupervised Domain-Adaptive Semantic Segmentation for Surgical Instruments Leveraging Dropout-Enhanced Dual Heads and Coarse-Grained Classification Branch

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical Robotics and Bionics 2025年

作者： Li, Ziqian Wang, Zhengyu Xu, Xinzhou Chen, Yongfa Schuller, Bjorn W. Hefei University of Technology School of Mechanical Engineering Hefei China Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing China Graz University of Technology Signal Processing and Speech Communication Laboratory Graz Austria Chair of Health Informatics Munich Germany Munich Data Science Institute Munich Germany Munich Center for Machine Learning Munich Germany Imperial College London GLAM – the Group on Language Audio and Music London United Kingdom

Accurate semantic segmentation for surgical instruments is crucial in robot-assisted minimally invasive surgery, mainly regarded as a core module in surgical-instrument tracking and operation guidance. Nevertheless, it is usually difficult for existing semantic surgical-instrument segmentation approaches to adapt to unknown surgical scenes, particularly due to their insufficient consideration for reducing the domain gaps across different scenes. To address this issue, we propose an unsupervised domain-adaptive semantic segmentation approach for surgical instruments, leveraging Dropout-enhanced Dual Heads and Coarse-Grained classification branch (D2HCG). The proposed approach comprises dropout-enhanced dual heads for diverse feature representation, and a coarse-grained classification branch for capturing complexities across varying granularities. This incorporates consistency loss functions targeting fine-grained features and coarse-grained granularities, aiming to reduce crossscene domain gaps. Afterwards, we perform experiments in crossscene surgical-instrument semantic segmentation cases, with the experimental results reporting the effectiveness for the proposed approach, compared with state-of-the-art semantic segmentation ones. © 2018 IEEE.

关键词： coarse-grained classification dropout enhancement Surgical instruments unsupervised domain-adaptive semantic segmentation

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An Optimization Algorithm for Service Composition Based on an Improved FOA

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Tsinghua science and technology 2015年第1期20卷 90-99页

作者： Yiwen Zhang Guangming Cui Yan Wang Xing Guo Shu Zhao the School of Computer Science and Technology Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

Large-scale service composition has become an important research topic in Service-Oriented Computing（SOC）. Quality of Service（Qo S） has been mostly applied to represent nonfunctional properties of web services and to differentiate those with the same functionality. Many studies for measuring service composition in terms of Qo S have been completed. Among current popular optimization methods for service composition, the exhaustion method has some disadvantages such as requiring a large number of calculations and poor scalability. Similarly,the traditional evolutionary computation method has defects such as exhibiting slow convergence speed and falling easily into the local optimum. In order to solve these problems, an improved optimization algorithm, WS FOA（Web Service composition based on Fruit Fly Optimization Algorithm） for service composition, was proposed, on the basis of the modeling of service composition and the FOA. Simulated experiments demonstrated that the algorithm is effective, feasible, stable, and possesses good global searching ability.

关键词： service composition Fruit Fly Optimization Algorithm（FOA） Quality of Service（QoS） index

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