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Deterministic-like data-driven discovery of stochastic differential equations via the Feynman–Kac formalism

The European Physical Journal Special Topics 2024年 1-21页

作者： Ma, Chaoxiang Huang, Cheng Cheng, Cheng Li, Xiuting The College of Informatics Huazhong Agriculture University and the China–Poland Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Wuhan People’s Republic of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Ministry of Education Key Lab of Intelligent Control and Image Processing Wuhan China

This paper develops a data-driven deterministic identification architecture for discovering stochastic differential equations (SDEs) directly from data. The architecture first generates deterministic data for stochastic processes using the Feynman–Kac formula, and gives a parabolic partial differential equation (PDE) associated with the SDE. Then, a sparse regression model is proposed to discover drift and diffusion terms in SDEs using PDE data-driven techniques, where a large candidate library of potential terms only for the drift and diffusion coefficients in SDEs need be constructed. To simultaneously infer the drift and diffusion terms, we proposed a sequential thresholded reweighted least-squares algorithm to solve the constructed sparse regression model. The main advantage of the proposed method is that on the one hand, theoretical and numerical identification results of PDEs can be used for SDEs, on the score, our SDE identification problem is translated into the parameter estimation problem of PDEs, on the other hand, the proposed algorithm is easily executed and can enhance the sparsity and accuracy. Through several classical SDEs and ordinary differential equations, the effectiveness of the proposed data-driven method is demonstrated, and several comparison experiments with state-of-the-art approaches is provided to illustrate the superiority of the developed algorithm.

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A multi-label front propagation approach for object segmentation

A multi-label front propagation approach for object segmenta...

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International Conference on Pattern Recognition

作者： H. Li A. Elmoataz J. Fadili S. Ruan Department of Electronics & Information Engineering State Education Commission Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology China GREYC-ISMRA CNRS Caen France LUSAC Cherbourg-Octeville France Equipe Image L.A.M.(EA 2075) Department GE&II IUT de Troyes Troyes France

For effective image segmentation methods, speed, accuracy and smoothness of the result are essential. In this paper, an iterative object segmentation approach is proposed based on minimal path theory. Each iterative step includes one morphological dilatation and one multi-label front propagation. A narrow band is obtained by dilating the current contour with the known size. A new contour is again formed by multi-label front propagation, which is based on minimal path theory. Its propagation speed is decided by the local image mean values together with the edge function. The final boundary is obtained automatically through finite iterations. This algorithm is a global optimization method. It is simple and fast with complexity O(N). The initial contour may be chosen freely. The multi-label front propagation guarantees continuity and smooth contours with the capability to handle topology changes. Furthermore, it is easy to extend to the 3D case. Some experimental results are also presented.

关键词： Object segmentation image segmentation Active contours Topology Computer vision Robust stability control engineering education Laboratories image processing intelligent control

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A nonlinear sliding mode observer for the estimation of temperature distribution in the planar solid oxide fuel cell stack

A nonlinear sliding mode observer for the estimation of temp...

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第五届世界氢能技术大会(WHTC2013)

作者： Huan Cheng Xi Li Jianhua Jiang Lin Zhang Jian Li Jie Yang Department of control science and Engineering Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Materials Science and Engineering State Key Laboratory of Material Processing and Die and Mould Technology Huazhong University of Science and Technology Wuhan 430074 China School of Mechanical and Electronic Information China University of Geosciences Wuhan 430074 China

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Leg hybrid rehabilitation based on hip-knee exoskeleton and ankle motion induced by FES

Leg hybrid rehabilitation based on hip-knee exoskeleton and ...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Xikai Tu Jian Huang Jiping He Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China School of Biological and Health Systems Engineering Arizona State University Tempe AZ USA School of Mechatronic Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509033652

To regain mobility, stroke patients need to receive repetitive and intensive therapy. Robot-assisted rehabilitation is an active area of research. Cheap robotic leg rehabilitation devices should be developed to meet the demands and assist most patients. A low cost hip-knee exoskeleton prototype powered by pneumatic muscles was developed. On this basis, Functional Electrical Stimulation (FES) induced paralyzed muscles to realize ankle joint rehabilitation training. As both of pneumatic muscle and FES induced muscle possess highly nonlinear characteristics, a sliding control algorithm called Chattering mitigation Robust Variable control (CRVC) was applied to leg hybrid rehabilitation. The combination of exoskeleton and FES is a promising way to reduce the cost and the complexity of designing hip-knee-ankle exoskeleton. The proposed hybrid method is verified by treadmill-based gait training experiments.

关键词： Muscles Exoskeletons Mathematical model Legged locomotion Iron Training

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An efficient moving target identification method

An efficient moving target identification method

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IEEE International Conference on intelligent processing Systems, ICIPS

作者： Nong Shang Tianxu Zhang Jiaxiong Peng Inst. for Pattern Recognition & Artifical Intelligence Huazhong Univ. of Sci. & Technol. Hubei China Institute for pattern Recognition and Artificial intelligence state Education commission Laboratory for Image processing and Intelligent control Huazhong University of Science슠and슠Technology Wuhan Hubei China

ISBN: (纸本)0780342534

Presents an efficient method which uses two neighboring frames in image sequences for target identification. Using statistical information about the background noise and candidate regions' noise after background registration, we can determine those candidate regions that have the same or similar noise distributions to the background's which should be background regions, and those candidate regions that have different noise distributions from the background's which should be the target region. In particular, when there is only one target in the image, we can simply determine that the candidate region whose noise distribution is most different from the background's is the true target.

关键词： Background noise image sequences

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Motor imagery Classification for Asynchronous EEG-Based Brain-Computer Interfaces

arXiv

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arXiv 2024年

作者： Wu, Huanyu Li, Siyang Wu, Dongrui The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science Technology Research Institute Shenzhen518063 China

Motor imagery (MI) based brain-computer interfaces (BCIs) enable the direct control of external devices through the imagined movements of various body parts. Unlike previous systems that used fixed-length EEG trials for MI decoding, asynchronous BCIs aim to detect the user's MI without explicit triggers. They are challenging to implement, because the algorithm needs to first distinguish between resting-states and MI trials, and then classify the MI trials into the correct task, all without any triggers. This paper proposes a sliding window prescreening and classification (SWPC) approach for MI-based asynchronous BCIs, which consists of two modules: a prescreening module to screen MI trials out of the resting-state, and a classification module for MI classification. Both modules are trained with supervised learning followed by self-supervised learning, which refines the feature extractors. Within-subject and cross-subject asynchronous MI classifications on four different EEG datasets validated the effectiveness of SWPC, i.e., it always achieved the highest average classification accuracy, and outperformed the best state-of-the-art baseline on each dataset by about 2%. © 2024, CC BY.

关键词： Self-supervised learning

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A programmable multi-channel stimulator for array electrodes in transcutaneous electrical stimulation

A programmable multi-channel stimulator for array electrodes...

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IEEE/ICME International Conference on Complex Medical Engineering, CME

作者： Qi Xu Tao Huang Jiping He Yizhao Wang Houlun Zhou Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Department of Control Science & Engineering Huazhong University of Science and Technology Wuhan China Harrington Department of Bioengineering Arizona State University Tempe AZ USA Tongji medical College Huazhong University of Science and Technology Wuhan China

Transcutaneous electrical stimulation (TES) has been applied to restore or maintain the muscle activity of paralyzed patients who suffer from spinal cord injuries and related neural impairments for several decades. In this paper, a portable and low-cost versatile stimulator for multichannel TES applications is described. The microcontroller-based programmable stimulator with four bipolar output channels send arbitrarily specified electrical pulses to the element in the electrode array for enabling the complex schemes of muscles. The amplitude and phase of each pulse in the stimulus sequence are independently variable, and the four channels are independently programmable, allowing a wide variety of stimulus patterns. We also designed an output circuit that can provide bi-phasic, voltage-regulated, charge-balanced outputs while avoiding the electrochemical erosion of electrode due to charge accumulation. The proposed stimulator has provided an opportunity for further study of a potential novel electrical stimulator with closed-loop stimulation paradigm suitable for a variety of FES applications, both for experimental and clinical studies.

关键词： Stimulated emission Algorithms Schottky diodes Biomedical optical imaging

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A Parallel Read-Write Circuit Design for Driving Memristor Crossbar Array

A Parallel Read-Write Circuit Design for Driving Memristor C...

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Neuromorphic Computing (ICNC), International Conference on

作者： Ningye Jiang Mingxuan Jiang Zhigang Zeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

Memristor crossbar array is considered as a promising circuit module for accelerating neural networks. Because the memristor is tunable and multi-state, it is important to design applicable Read-Write (RW) circuit for driving memristor crossbar array. In this paper, a novel RW circuit based on analog circuits is proposed for tuning memristors in high-dimensional array parallelly, which is scalable and low-overhead. The standalone RW circuit schematic is presented for reading/writing single memristor and verified in circuit simulation. Then, we extend and apply this circuit into a two-dimensional memristor crossbar array. The performance of memristor crossbar array controlled by designed RW circuits is verified via the simulations under various machine learning datasets. The comparison with related works is presented, which demonstrates the advantages of the proposed RW circuit regarding overhead and anti-error.

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Derivation languages of splicing P systems 12th

Derivation languages of splicing P systems

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12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Mahalingam, Kalpana Paul, Prithwineel Song, Bosheng Pan, Linqiang Subramanian, K.G. Department of Mathematics Indian Institute of Technology Madras Chennai600036 India Key Laboratory of Image Information Processing Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom

ISBN: (纸本)9789811071782

Labelled splicing P systems are distributed parallel computing models, where sets of strings that evolve by splicing rules are labelled. In this work, we consider labelled splicing systems with the following modifications: (i) The strings in the membranes are present in arbitrary number of copies;(ii) the rules in the regions are finite in number. Results on the language family generated by the labelled splicing system in comparison with the language families of the Chomsky hierarchy, including recursively enumerable languages, are obtained, by involving only either one or two membranes in the P systems considered. © Springer Nature Singapore Pte Ltd 2017.

关键词： Distributed computer systems

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Optimizing Binary Sequence Excitation Signals for Rapid Impedance Spectrum Measurement in Proton Exchange Membrane Fuel Cells

Optimizing Binary Sequence Excitation Signals for Rapid Impe...

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第43届中国控制会议

作者： Jingzhi Lei Chuang Sheng Jingjing Wang Liansong Yu Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology State Grid Electric Power Research Institute Wuhan Nanrui Limited Liability Company Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

With the increasing demand for efficient and reliable renewable energy sources,Proton Exchange Membrane Fuel Cells(PEMFCs) have emerged as a promising *** experiments demonstrate that Electrochemical Impedance Spectroscopy(EIS) effectively differentiates various states of *** broadband signals as testing excitations significantly reduces EIS measurement time,facilitating real-time monitoring of PEMFCs' health under dynamic *** signal design requires maintaining adequate amplitude across frequency components for noise resistance while minimizing signal peak value to reduce operational *** paper introduces an EIS simulation environment,leveraging PEMFCs' impedance and electrochemical noise *** focuses on optimizing the excitation signal's amplitude-frequency distribution using discrete interval binary *** results indicate that our method achieves minimal perturbation amplitude while preserving measurement accuracy in amplitude-frequency signal design.

关键词： Proton exchange membrane fuel cell Electrochemical impedance spectroscopy Electrochemical noise Excitation signal optimization

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