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A Nested Neighborhood PSO Algorithm for Multi-modal Function Optimization

A Nested Neighborhood PSO Algorithm for Multi-modal Function...

引用

World Congress on intelligent Control and automation (WCICA)

作者： Guangyu Lian Chundi Mu Zengqi Sun State Key Laboratory of Intelligent Technology and System Tsinghua University Beijing China Department Automation Tsinghua University Beijing China

In PSO algorithm, a nested neighborhood model was proposed for multi-modal function optimization. First, a local structure was constructed for each particle under a predefined Euclidian distance measure (called peak-granularity). Then a nesting mechanism was presented to connect the local-best particles resulting in a nested neighborhood chain. Some concepts, neighbor operator, peak neighbor and nesting counter were introduced to describe the mechanism. Based upon the mechanism, local-best information can be shared by all the particles on the neighborhood chain. This effectively improves the convergence performance of the particle swarm. And the peak-granularity can be kept small to locate more optimal basins of the function. Several benchmark functions are adopted to verify the performance

关键词： Particle swarm optimization automation Sun intelligent systems Electronic mail Particle measurements Counting circuits Convergence intelligent control

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A Novel SINS/GPS Integration Algorithm Based on Neural Networks

A Novel SINS/GPS Integration Algorithm Based on Neural Netwo...

引用

World Congress on intelligent Control and automation (WCICA)

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

SINS/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 SINS. Most of the present navigation systems rely on Kalman filtering methods to fuse data. Present Kalman filtering SINS/GPS integration techniques have several inadequacies related to sensor error model, immunity to noise and observability. This paper aims at introducing a novel SINS/GPS integration algorithm utilizing Hopfield neural network. This method obtains the optimal state estimation by minimizing the energy function of the Hopfield neural network. Furthermore this algorithm relaxes the assumptions made by the Kalman filter so that it is more versatile. Simulation results show that the new integration algorithm 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 integration algorithm can improve the navigation guidance accuracy, real time ability and practicability of the SINS/GPS

关键词： Silicon compounds Global Positioning system Neural networks Navigation Hopfield neural networks Kalman filters Filtering Fuses Observability state estimation

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Multi-Biometrics Fusion for Identity Verification

Multi-Biometrics Fusion for Identity Verification

引用

International Conference on Pattern Recognition

作者： Chang Shu Xiaoqing Ding State Key laboratory of Intelligent Technology and System Department of Electronic Engineering Tsinghua University Beijing China

In this paper, we accomplish matching score level fusion of multi-biometrics. In order to solve the incomparability among different classifiers' outputs, adaptive confidence transform (ACT) is introduced to convert the raw outputs of different classifiers to the estimates of posteriori probabilities conforming to different users. These posteriori probabilities are then combined using several fusion methods. Experiments conducted on a database (including face, iris, online signature and offline signature traits) of about 100 users indicate that for the same fusion method, ACT based normalization generally results in better verification performance and is more robust compared to other normalization methods. Effects of different normalization and fusion methods on combination of "strong" and "weak" classifiers are also examined

关键词： Databases Iris Noise robustness Laboratories intelligent systems Biometrics Protection Fusion power generation Arithmetic Pattern matching

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3D+2D Face Localization Using Boosting in Multi-Modal Feature Space

3D+2D Face Localization Using Boosting in Multi-Modal Featur...

引用

International Conference on Pattern Recognition

作者： Feng Xue Xiaoqing Ding State Key Laboratory of Intelligent Technology and System Department of Electronic Engineering Tsinghua University Beijing China

Facial feature extraction is important in many face-related applications, such as face alignment for recognition. Recently, boosting-based methods have led to the state-of-the-art face detection and localization systems. In this paper, we propose a multi-modal boosting algorithm to integrate 3D (range) and 2D (intensity) information provided from a facial scan to detect the face and feature point (nose tip, eyes center). Given a face scan, Gauss and mean curvature are calculated. Face, nose and eyes detectors are trained in color images and curvature maps features space using AdaBoost. As a result, a fully automatic multi-modal face location system is developed. The performance evaluation is conducted for the proposed feature extraction algorithm on a publicly available data-base, containing 4007 facial scans of 466 subjects

关键词： Boosting Face detection Nose Eyes Facial features Data mining Face recognition Gaussian processes Detectors Color

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INS/GPS Integrated Navigation Uncertain system state Estimation Based on Minimal Variance Robust Filtering

INS/GPS Integrated Navigation Uncertain System State Estimat...

引用

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

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

INS/GPS integrated navigation systems are used for positioning and attitude determination in a wide range of applications. Combining INS and GPS organically, we can get an integrated navigating system which can overcome the respective defects of the two systems and develop their advantages to form a complementary structure at the same time. GPS measurements can be used correct the INS and sensor errors to provide high accuracy real-time navigation (Farrell, 1998). The integration of GPS and INS measurements is usually achieved using a Kalman filter. But, usually uncertainties exist in INS/GPS integrated real systems, which may cause filtering to divergence for classical Kalman filter. In order to solve this problem, a robust filter with minimal variance is addressed by this paper

关键词： Global Positioning system Navigation Uncertain systems state estimation Robustness Filtering Position measurement systems engineering and theory Application software automation

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A Facial Expression Model for Human-Like Agent

A Facial Expression Model for Human-Like Agent

引用

IEEE Conference on Robotics, automation and Mechatronics

作者： Bin Yang Peifa Jia State Key Laboratory of Intelligent Technology and System Department of Computer Science Tsinghua University Beijing Beijing China

A major unsolved problem in human-like agent is the construction and application of realistic human facial expression models. Human-like agents should interact with human by recognizing human facial expression and synthesizing facial expressions to show their emotional states. However there is no a uniform model for both recognition and synthesis of facial expression. In this paper, we present a model for solving this challenging task. First, we setup a muscle-based facial model and use muscles' contraction as controlling factors because all the facial actions are driven by the muscles. An orthogonal facial expression space is constructed by regarding each controlling factor as a dimension. Then muscles' contractions are calculated from facial images to construct the facial vector. Thus the facial vector can be used on the facial expression synthesis system of human-like agent. In this paper, we also present a facial function to describe the dynamic procedure of facial expressions. Last, this paper points out the direction of future work

关键词： Muscles Humans Facial animation Face recognition intelligent agent intelligent systems Computer science Control system synthesis MPEG 4 Standard Skin

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An Adaptive Filter for INS/GPS Integrated Navigation system

An Adaptive Filter for INS/GPS Integrated Navigation System

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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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Visual Object Recognition in Diverse Scenes with Multiple Instance Learning

Visual Object Recognition in Diverse Scenes with Multiple In...

引用

2006 IEEE/RSJ International Conference on intelligent Robots and systems

作者： Dong Wang Bo Zhang Jianwei Zhang Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and System Tsinghua University Beijing China TAMS Department of Informatik University of Hamburg Hamburg Germany

Visual object recognition is important to the robot industry and is a prerequisite for other robot functionalities, such as grasping and manipulation. Object representation and a learning technique are two indispensable parts for this demanding task while arbitrary object appearance and diverse scenes with cluttered background are two great challenges. However, compared with object representation, the learning technique is less developed to deal with these challenges. This paper extends the multiple instance learning (MIL) technique to the multi-class classification scenario and introduces this multi-class MIL framework to the object recognition domain for the first time. This framework is independent of object representation and is useful for object/background discrimination in unseen scenes. Preliminary experiments show that it compares favorably with the supervised learning approach which takes whole images as the classifier training input

关键词： Object recognition Layout intelligent robots Supervised learning Unsupervised learning Iterative algorithms Service robots Robot sensing systems Computer science intelligent systems

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Research on the Surface EMG Signal for Human Body Motion Recognizing Based on Arm Wrestling Robot

Research on the Surface EMG Signal for Human Body Motion Rec...

引用

International Conference on Information and automation (ICIA)

作者： Zhen Gao Jianhe Lei Quanjun Song Yong Yu Yunjian Ge Department of Automation University of Science and Technology Hefei Anhui China State Key laboratory of Robot Sensing System Chinese Academy and Sciences Hefei Anhui China

In this paper, the surface electromyographic (EMG) signals is acquired from the upper limb when the experimenter competes with the arm wrestling robot (AWR) which is integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3D MEMS accelerometer, and USB camera. The arm wrestling robot (AWR) is intended to play arm wrestling game with human on a table with pegs for entertainment and human upper limbs muscle modeling. As the EMG signal is a measurement of the anatomical and physiological characteristic of the given muscle, the macroscopical movement patterns of the human body can be classified and recognized. By using the method of wavelet packet transformation (WPT), the high-frequency noises can be eliminated effectively and the characteristics of EMG signals can be extracted. Auto-regressive (AR) model is adopted to effectively simulate the stochastic and non-stationary time sequences using a series of AR coefficients with a typical order. Artificial neural network (ANN) is utilized to distinguish the different force levels and game grades in the scenario of arm-wrestling. To advance the training speed and accurate rate of the motion pattern classification, back-propagation (BP) neural network based on adaptive learning rate algorithm (ALR) is introduced. The advantage of ALR algorithm compared with standard BP algorithm is confirmed by experiments

关键词： Electromyography Humans Robot sensing systems Biological system modeling Artificial neural networks Muscles Elbow Wrist Force sensors Servomechanisms

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SINS/GPS integrated system state estimation based on covariance assignment

SINS/GPS integrated system state estimation based on covaria...

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systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on

作者： Hang Shi Jihong Zhu Haiyan Tian State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technology Tsinghua University Beijing China College of Mathematics and Information Science Hebei Normal University Shijiazhuang China

ISBN: (纸本)0780393953

SINS and GPS are widely used. Combining SINS and GPS organically, we can get an reliable integrated navigating system which can overcome the respective defects of the two systems, including signal blockage for GPS and growth of position errors with time for SINS, and develop their advantages to form a complementary structure at the same time. On the basis of using the SINS/GPS integrated navigation system, we introduce the covariance assignment state estimation algorithm not only to enhance the navigational capability and accuracy, but also enhance the robustness of the navigation system.

关键词： Global Positioning system covariance analysis inertial navigation state estimation Global Positioning system covariance assignment integrated system state estimation strap-down inertial navigation system

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