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An Adaptive Filter for INS/GPS Integrated Navigation system

An Adaptive Filter for INS/GPS Integrated Navigation System

引用

Computational Engineering in systems Applications, CESA, IMACS Multiconference on FLAGGED

作者： Hang Shi Zhou Wu Baosheng Liu State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technology Tsinghua University Beijing China School of Mechatronical Engineering and Automation National University of Defense Technology Changsha China Department of Automation Tsinghua University Beijing China

The integrated navigation system, specially the system based on GPS and INS, is a leading trend of navigation technology, and some of typical integrated navigation systems have been developed and tested in the past few years (Farrell, 1998). But due to the complex application circumstance, it is difficult to describe the noise statistical property accurately. In this paper, a modified adaptive filter algorithm is presented for INS/GPS integrated navigation system. At first, an improved Kalman filter and H infin robust filter are explicitly represented for INS/GPS integrated navigation system. Meanwhile, a standard for judging that whether the filter trends to divergence is proposed to combine the two methods. Aiming at the detail position/velocity integrated mode, the computer simulation result of INS/GPS integrated navigation show that this method can restrain the divergence effectively and has better adaptive ability

关键词： Adaptive filters Global Positioning system Noise robustness Filtering algorithms Automation Noise reduction Aircraft navigation systems engineering and theory Application software Laboratories

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EMG signal classification for myoelectric teleoperating a dexterous robot hand

EMG signal classification for myoelectric teleoperating a de...

引用

2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Wang, J.Z. Wang, R.C. Li, F. Jiang, M.W. Jin, D.W. Division of Intelligent and Biomechanical System State Key Laboratory of Tribology Tsinghua University Beijing 100084 China

ISBN: (纸本)0780387406

This paper details a strategy of discriminating finger motions using surface electromyography (EMG) signals, which could be applied to teleoperating a dexterous robot hand or controlling the advanced multi-fingered myoelectric prosthesis for hand amputees. Finger motions discrimination is the key problem in this study. Thus the emphasis is put on myoelectric signal processing approaches in this paper. The EMG signal classification system was established based on the surface EMG signals from the subject's forearm. Four pairs of electrodes were attached on the subjects to acquire the signals during six types of finger motions, i.e. thumb extension, thumb flexion, index finger extension, index finger flexion, middle finger extension, and middle finger flexion. In order to distinguish these finger motions. A combination of autoregressive (AR) model and an Artificial Neural Network (ANN) was used in the system. The discrimination procedure consists of two steps. Firstly, the AR model is used to preprocess the surface EMG signals to reduce the scale of the data. These data will be imported into the myoelectric pattern classifier. Secondly the coefficients of AR model are imported into the ANN to identify the finger motions. The experimental results show that the discrimination system works with satisfaction. © 2005 IEEE.

关键词： Electromyography

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The investigation on sEMG of lower extremity when a slip occurs in level walking

The investigation on sEMG of lower extremity when a slip occ...

引用

2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Yang, JianKun Jin, DeWen Wang, RenCheng Zhang, JiChuan Ji, LinHong Fang, Xin Zhou, DaWei Division of Intelligent and Biomechanical System State Key Laboratory of Tribology Tsinghua University Beijing China Beijing China

ISBN: (纸本)0780387406

The purpose of the present study was to determine the relationship between the surface electromyography (sEMG) variables and slip events using principal component analysis (PCA). Ten healthy young adults were required to walk on the oily surface on a self-selected comfortable pace. The sEMG signals of lower extremity muscles were recorded and analyzed, while kinematics data was recorded to assist slip definitions. When ten variables (seven in time domain and three in frequency domain) were considered in the PCA, the results indicated that 1) three most important principal components could explain more than 85% of the variation in the entire data set;2) some variables should be especially noticed such as muscle power, the mean frequency, the median frequency and the amplitude amount exceeding the mean value. © 2005 IEEE.

关键词： Electromyography

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A high performance face recognition system based on a huge face database

A high performance face recognition system based on a huge f...

引用

International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Meng, Kai Su, Guang-Da Li, Cong-Cong Fu, Bo Zhou, Jun State Key Laboratory of Intelligent Technology and System Electronic Engineering Department Tsinghua University Beijing 100084 China

ISBN: (纸本)078039092X

This paper presents a high performance face recognition system, in which the face database has a large amount of 2.5 million faces. Huge as the face database is, the recognition processes in ordinary ways meets with great difficulties: the identification rate of most algorithms may decline significantly;meanwhile, querying on a large scale database may be quite time-consuming. In our system, a special distributed parallel architecture is proposed to speed up the computation. Furthermore, a multimodal part face recognition method based on principal component analysis (MMP-PCA) is adopted to perform the recognition task, and the MMX technology is introduced to accelerate the matching procedure. Practical results prove that this system has an excellent performance in recognition: when searching among 2,560,000 faces on 6 PC servers with Xeon 2.4GHz CPU, the querying time is only 1.094s and the identification rate is above 85% in most cases. Moreover, the greatest advantage of this system is not only increasing recognition speed but also breaking the upper limit of face data capacity. Consequently, the face data capability of this system can be extended to an arbitrarily large amount. © 2005 IEEE.

关键词： Face recognition

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A study on fitts' law based gait symmetric evaluation and it's clinic application

A study on fitts' law based gait symmetric evaluation and it...

引用

2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Wang, Rencheng Zhang, Meiqin Deng, Xiaonan Jin, Dewen Wang, Maobin Li, Guangqing Division of Intelligent and Biomechanical System State Key Laboratory of Tribology Tsinghua University Beijing 100084 China Division of Intelligent and Biomechanical System State Key Laboratory of Tribology Tsinghua University Beijing Xuanwu Hospital Capital University of Medical Sciences Beijing 100053 China

ISBN: (纸本)0780387406

Symmetry, one of the prominent characters of normal human gait, could be destroyed by some special or abnormal factors such as barrier spanning, walking impediment, etc. Therefore, it becomes an important factor used to evaluate qualities and functions of walking. In this paper, the fitts' law based symmetry index calculation is introduced and its application in clinic test is also reported. The results show that the fitts' law based index is effective in clinic evaluation. © 2005 IEEE.

关键词： Gait analysis

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Influence of shoe-heel height of the trans-tibial prosthesis on static standing biomechanics

Influence of shoe-heel height of the trans-tibial prosthesis...

引用

2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Li, Xiaobing Jia, Xiaohong Dou, Peng Fang, Lidan Department of Precision Instruments Tsinghua University China Division of Intelligent and Biomechanical System State Key Laboratory of Tribology Tsinghua University Beijing 100084 China

ISBN: (纸本)0780387406

Shoe-heel height has great influence on lower-limb amputees' biomechanics during static standing. This article mainly considers the load line of the prosthetic side in the sagittal plane and the electromyogram (EMG) data of the lower limb muscles. The results indicate that the load line and the EMG are greatly influenced by the shoe-heel height, however, the amputee subconsciously adjusts his standing manner to make himself more comfortable and natural. This will provide references for prosthesis design and alignment setting. © 2005 IEEE.

关键词： Prosthetics

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Reinforcement learning control for ship steering using recursive least-squares algorithm

Reinforcement learning control for ship steering using recur...

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作者： Shen, Zhi-Peng Guo, Chen Yuan, Shi-Chun Lab. of Simulation and Control of Navigation Systems Dalian Maritime Univ. Dalian 116026 China State Key Laboratory of Intelligent Technology and System Tsinghua University Beijing 100084 China

ISBN: (纸本)008045108X

Recursive least-squares temporal difference algorithm (RLS-TD) is deduced, which can use data more efficiently with fast convergence and less computational burden. Reinforcement learning based on recursive least-squares methods is applied to ship steering control, as provides an efficient way for the improvement of ship steering control performance. It removes the defect that the conventional intelligent algorithm learning must be provided with some sample data. The parameters of controller are on-line learned and adjusted. Simulation results show that the ship course can be properly controlled in case of the disturbances of wave, wind, current. It is demonstrated that the proposed algorithm is a promising alternative to conventional autopilots. Copyright © 2005 IFAC.

关键词： Learning algorithms

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INS/GPS Integrated system state Estimation Based on Hopfield Neural Network

INS/GPS Integrated System State Estimation Based on Hopfield...

引用

2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Hang Shi Jihong Zhu Zengqi Sun State Key Laboratory of Intelligent Technology and System Department of Computer Science and TechnologyTsinghua University

This paper aims at introducing state estimation in INS/GPS integrated system utilizing Hopfield neural ***/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings,including signal blockage for GPS and growth of position errors with time for *** of the present navigation systems rely on Kalman filtering methods to fuse *** Kalman filtering INS/GPS integration techniques have several inadequacies related to sensor error model,immunity to noise and *** method presented in this paper,obtains the optimal state estimation by minimizing the energy function of the Hopfield neural *** new estimator relaxes the assumptions made by the Kalman filter so that it is more *** results show that the new estimator performs similarly to the Kalman *** it has some advantages such as fast convergence,unbias and high precision during fusion process,despite of the inaccurate modeling errors,system disturbance,observation errors,and even the shortage of *** as the parallel computational mode and easily carried out in hardware of the Hopfield neural network,this fusion method can improve the navigation guidance accuracy,real time ability and practicability of the INS/GPS.

关键词： Hopfield INS/GPS Integrated system state Estimation Based on Hopfield Neural Network GPS

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A high performance face recognition system based on a huge face database

A high performance face recognition system based on a huge f...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Meng Guang-Da Su Cong-Cong Li Bo Fu Jun Zhou The State Key Laboratory of Intelligent Technology and System Electronic Engineering Department Tsinghua University Beijing China

This paper presents a high performance face recognition system, in which the face database has a large amount of 2.5 million faces. Huge as the face database is, the recognition processes in ordinary ways meets with great difficulties: the identification rate of most algorithms may decline significantly; meanwhile, querying on a large-scale database may be quite time-consuming. In our system, a special distributed parallel architecture is proposed to speed up the computation. Furthermore, a multimodal part face recognition method based on principal component analysis (MMP-PCA) is adopted to perform the recognition task, and the MMX technology is introduced to accelerate the matching procedure. Practical results prove that this system has an excellent performance in recognition: when searching among 2,560,000 faces on 6 PC servers with Xeon 2.4 GHz CPU, the querying time is only 1.094 s and the identification rate is above 85% in most cases. Moreover, the greatest advantage of this system is not only increasing recognition speed but also breaking the upper limit of face data capacity. Consequently, the face data capability of this system can be extended to an arbitrarily large amount.

关键词： Face recognition Databases Large-scale systems Concurrent computing Data security Computer networks Machine learning algorithms Principal component analysis Acceleration Laboratories

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JNS/GPS Integrated system state Estimation Based on Hopfield Neural Network

JNS/GPS Integrated System State Estimation Based on Hopfield...

引用

International Conference on Neural Networks and Brain (ICNNB)

作者： Hang Shi Jihong Zhu Zengqi Sun State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technology Tsinghua University Beijing China

This paper aims at introducing state estimation in INS/GPS integrated system utilizing Hopfield neural network. INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Most of the present navigation systems rely on Kalman filtering methods to fuse data. Present Kalman filtering INS/GPS integration techniques have several inadequacies related to sensor error model, immunity to noise and observability. The method presented in this paper, obtains the optimal state estimation by minimizing the energy function of the Hopfield neural network. This new estimator relaxes the assumptions made by the Kalman filter so that it is more versatile. Simulation results show that the new estimator performs similarly to the Kalman filter. Furthermore it has some advantages such as fast convergence, unbias and high precision during fusion process, despite of the inaccurate modeling errors, system disturbance, observation errors, and even the shortage of observation. Also as the parallel computational mode and easily carried out in hardware of the Hopfield neural network, this fusion method can improve the navigation guidance accuracy, real time ability and practicability of the INS/GPS

关键词： Global Positioning system state estimation Hopfield neural networks Navigation Kalman filters Filtering Fuses Observability Computational modeling Convergence

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