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作者： Wu, Jun Wang, Yongji Huang, Jian Xing, Kexin Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering HuaZhong University of Science and Technology Wuhan Hubei China

In this paper, the Pneumatic Muscle (PM) as actuator is investigated. The PM model is established by using a phenomenological model consisting of a contractile element, a spring element, and a damping element in parallel. Unlike the previous study, we fully consider the different characteristics of PM model in different pressure ranges, especially in low pressure range. In order to test the effectiveness of our PM modelling, the Sliding Mode control (SMC) is applied. For the purpose of improving the tracking accuracy, self-adaptation and robustness of PM control, Sliding Mode control with Fuzzy Compensator (FCSMC) is developed to make PM system track a desired trajectory within a guaranteed accuracy even though there are modelling uncertainties, friction, disturbance, and so on. Based on the Lyapunov theory, the stability criterion under FCSMC control strategy for PM system is established. The experimental results demonstrate the validity of PM modelling as well as indicate the effectiveness of the proposed FCSMC method. Copyright © 2012 Inderscience Enterprises Ltd.

关键词： Sliding mode control

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One-time-pads encryption in the tile assembly model

One-time-pads encryption in the tile assembly model

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作者： Chen, Zhihua Xu, Jin Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Recent research has demonstrated that the ultra-scale computation by self-assembly DNA tiles can be implemented in the laboratory. One of the significant applications is the DNA-based cryptography systems. In this paper, we detail procedures for the DNA-based One-Time-Pads (OTP) cryptography, which is in principle unbreakable. In order to implement the whole encrypting and decrypting processes, we propose four tile systems: encrypting system, ciphertext extracting system, key extracting system and decrypting system. All the tile systems use θ(1) input tiles and compute in θ(n) steps according to the length of the input massage. The method of implementing the DNA OTP encryption extends the self-assemble tile models and achieves the real randomness in the DNA OTP. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Cryptography

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SAR image segmentation based on immune greedy spectral clustering

SAR image segmentation based on immune greedy spectral clust...

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Gou, S.P. Zhang, J. Jiao, L.C. Key Laboratory of Intelligent Perception and Image Understanding for the Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

In this paper we propose a novel spectral clustering algorithm called Immune Greedy Spectral Clustering Algorithm, which introduces immune clone selection algorithm instead of greedy selection to choose a subset before greedy spectral embedding without any prior experiment knowledge. As we know, Nyström algorithm is a random selecting method which depends so much on the selecting result so that the clustering result fluctuates obviously. Greedy spectral clustering algorithm acquires a subset called dictionary by greedy selection algorithm so that the result could be more stable and better. However, to choose an appropriate input tolerance, we need prior experiment knowledge about the relationship between tolerance and select number. Moreover, since the criterion used for greedy selection is the distance in feature space between a candidate example and its projection on the subspace spanned by selected examples, we need to compute every example point one by one to get the error of using the selected examples to approximate the candidate example and then decide whether to choose it. So the time expense increases inevitable. Considering all above, we present a new method called Immune Greedy Spectral Clustering Algorithm. The experimental results show that Immune Greedy Spectral Clustering Algorithm need no prior experiment knowledge and could save time compared with greedy spectral clustering while getting a better accuracy rate compared with Nyström algorithm. ©2009 IEEE.

关键词： Cloning

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Echo state network-based internal model control for pneumatic muscle system

Echo state network-based internal model control for pneumati...

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2011 International Conference on Electrical, information Engineering and Mechatronics, EIEM 2011

作者： Wu, Jun Wang, Yongji Huang, Jian Zhou, Hanying Cai, Hong Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9781447124665

Pneumatic muscle (PM) has strong time varying characteristic. The complex nonlinear dynamics of PM system poses problems in achieving accurate modeling and control. To solve these challenges, we propose an echo state network (ESN)-based internal model control (IMC) for PM system in this paper. Here, ESN is employed for identifying the plant model and constructing controller. Recursive least squares (RLS) is used for the online update of ESN. The ESN-based IMC fully embodies the virtues of ESN and IMC. It can build high accurate plant model without detailed model information, as well as attain strong robustness by online self-tuning of controller and internal model. Experiment demonstrates the effectiveness of the proposed control algorithm. The results show that ESNBIMC achieves satisfactory tracking performance. © 2012 Springer-Verlag London Limited.

关键词： controllers

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Fuzzy PID control of a wearable rehabilitation robotic hand driven by pneumatic muscles

Fuzzy PID control of a wearable rehabilitation robotic hand ...

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20th Anniversary MHS 2009 and Micro-Nano Global COE - 2009 International Symposium on Micro-NanoMechatronics and Human Science

作者： Wu, Jun Huang, Jian Wang, Yongji Xing, Kexin Xu, Qi Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9781424450954

Intensive task-oriented repetitive physical therapies need be provided by individualized interaction between the patients and the rehabilitation specialists to improve hand motor performance for those survived from stoke and traumatic brain injury. The goal of this research is to develop a novel wearable device for robotic assisted hand repetitive therapy. We designed a pneumatic muscle (PM) driven therapeutic device that is wearable and provides assistive forces required for grasping and finger extension. The robot has two distinct degrees of freedom at the thumb and all other fingers. The embedded sensors can feedback position and force information for robot control and quantitative evaluation of task performance. It is potential of providing supplemental at-home therapy in addition to in the clinic treatment. To realize the trajectory tracking control, a fuzzy PID controller is designed for the proposed device. The experimental results show angle tracking control of the robotic hand using the fuzzy PID controller has better performance than that using a conventional PID controller. ©2009 IEEE.

关键词： Wearable technology

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Research on Autonomous Foot Movement Recognition Based on SVM 2022

Research on Autonomous Foot Movement Recognition Based on SV...

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7th International Conference on Multimedia and image processing, ICMIP 2022

作者： Meng, Tongning Zhao, Li Zhang, Zhiwen He, Xinglin Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Intelligent Information Processing Tianjin300222 China

ISBN: (纸本)9781450387408

In order to improve the effectiveness of rehabilitation of stroke patients, active training can be used to treat and recover the patient's foot dyskinesia. Recognizing the different movement characteristics of the feet is an important part of the active rehabilitation of stroke patients. In this paper, the EMG signals of different movements of the right foot are classified and studied. The EMG signals of three different movement states of the foot resting state, foot stretched 15° and foot stretched 45° are collected, absolute mean and filter common space mode were used for feature extraction of EMG signal, and support vector machine (SVM) was used for classification and recognition after extraction. The experimental results show that the classification accuracy rate of resting state-foot-stretched 45° is 89.9%, which exceeds the classification accuracy rate of resting state-foot-stretched 15° of 86.8%. It shows that when the subjects stretch the foot at 45°, more motion units are activated and the characteristics are more obvious than when the feet are stretched at 15°. Therefore, by classifying the characteristics of EMG signals and identifying different autonomic movements of feet, it can be used as the basis for rehabilitation treatment of stroke patients. At the same time, the average classification accuracy of 15°-45 ° and the resting state-15 °-45 ° is above 80%, which confirms the feasibility of the signal processing method and support vector machine classification algorithm used in this paper for the study of automatic foot motion recognition. © 2022 ACM.

关键词： Support vector machines

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Contour Extraction via Contextual Modulation

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电子学报(英文版) 2009年第2期18卷 329-331页

作者： HUANG Wentao JIAO Licheng XU Yuelei SUN Ye JIA Jianhua Institute of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi＇an 710071 China Department of Avionics Engineering Engineering College of Air Force Engineering University Xi＇an 710038 China

Contour extraction is an important task in image processing and computer vision. The contextual modulation is a universal phenomenon in the primary visual cortex (VI). A biologically motivated computational model is presented for contour extraction in this paper. Two mechanisms of contextual modulation, surround suppression and collinear facilitation, are integrated in this model. We obtain good results via this model to extract contours from images with noise and texture backgrounds. This work provides a biologically motivated approach with great potential for computer vision.

关键词：轮廓提取调制语境动力计算模型计算机视觉初级视觉皮层图像处理图像轮廓

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A novel DNA computing model based on RecA-mediated triple-stranded DNA structure

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Progress in Natural Science:Materials International 2007年第6期17卷 708-711页

作者： Fang Gang1, Zhang Shemin2, Dong Yafei1 and Xu Jin1(1. The key laboratory of image processing and intelligent control, Department of control Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China 2. Shaanxi University of Technology, Hanzhong 723000, China) [a]The Key Laboratory of Image Processing and Intelligent Control Department of Control Science & Engineering Huazhong University of Science and Technology Wuhan China [b]Shaanxi University of Technology Hanzhong China

The field of DNA computing emerged in 1994 after Adleman’s paper was published. Henceforth,a few scholars solved some noted NP-complete problems in this way. And all these methods of DNA computing are based on conventional Watson-Crick hydrogen bond of doublehelical DNA molecule. In this paper, we show that the triple-stranded DNA structure mediated by RecA protein can be used for solving computational problems. Sequence-specific recognition of double-stranded DNA by oligonucleotide-directed triple helix (triplex) formation is used to carry out the algorithm. We present procedure for the 3-vertex-colorability problems. In our proposed procedure, it is suggested that it is possible to solve more complicated problems with more variables by this model.

关键词： DNA computing 3-vertex-colorability problem.

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A novel computational approach to predict activity of nuclear export signals

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Journal of Computational and Theoretical Nanoscience 2015年第12期12卷 6016-6019页

作者： Chen, Zhihua Zhang, Pan Wu, Tingfang Shi, Xiaolong Wang, Xun Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China College of Computer and Communication Engineering China University of Petroleum QingdaoShandong266580 China

A nuclear export signal (NES) is a sequence of amino acids, which is a protein localization signal, and contributes to regulate localization of cellular proteins. In recent peering works, activity of NESs were introduced in computational methods, which perform significantly well in identifying unknown NESs even from huge datasets, but suffer from a shortage that only a small number of NESs are associated with experimental verified active scores. In this work, we propose a novel computational method to predict active score of NESs. Specifically, we firstly abstract relevant features to NES activity, and then construct a mathematical model based on principal component analysis (PCA) to find each feature's contribution to activity. In this way, a method to calculate active score of unknown NESs is achieved. In data experiments, it is obtained that our method can achieve accuracy rate 80%. The activity of an unknown NES candidate can give us a preliminary understanding of it, and can be used to identify positive NESs from the negative ones. To the best acknowledge of the authors, this is the first time computational method is proposed to predict NESs' activity. Copyright © 2015 American Scientific Publishers All rights reserved.

关键词： Computational methods

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Transfer network learning based remote sensing target recognition

Transfer network learning based remote sensing target recogn...

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Gou, Shuiping Wang, Yuqin Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding for the Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

The target recognition accuracy of remote sensing images is not satisfied. The labels of images acquisition and recollecting are difficult and expensive. In order to solve the problem, we introduce transfer learning into Network Boosting algorithm (NB) and propose Transfer Network Learning algorithm (TNL), in which other out-date data are reused to instruct the remote sensing target recognition. TNL is suitable to improve the performance of remote sensing target recognition, in which instances transfer learning is adopted for domain adaptation. The experimental results on the MSTAR SAR data set and remote sensing data set including two-class planes show that the proposed algorithm has better performance and achieves different domains learning. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Learning algorithms

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