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A New Architecture to Execute CAs-Based Path-Planning Algorithm in Mobile Robots

A New Architecture to Execute CAs-Based Path-Planning Algori...

引用

International Conference on Mechatronics (ICM)

作者： Adel Akbarimajd Caro Lucas Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Iran Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran Iran

Several path-planning algorithms for mobile robots have been introduced. Proper architectures for mobile robots to implement the path-planning algorithms are also of interest. If the mobile robots are to perform complicated tasks including complex sensing and planning operations and have accepted performance, must be autonomous: capable of acquiring information and performing tasks without programmatic intervention. In this paper we employ a layered architecture for mobile robots to perform our previously introduced cellular automata based path planning technique. It employs an abstraction approach which makes the complexity manageable. The architecture has an important feature which is its internal artifacts; it has some beliefs about the world and these beliefs are represented in artifacts and most actions are planned and performed with respect to these artifacts

关键词： Path planning Mobile robots Robot kinematics Content addressable storage Lattices computer architecture Orbital robotics Automata Intelligent sensors Robotics and automation

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ROBUST SPACE-VARIANT SUPER-RESOLUTION

ROBUST SPACE-VARIANT SUPER-RESOLUTION

引用

2006 IET International Conference on Visual Information engineering

作者： K.V. Suresh A.N. Rajagopalan Image Processing and Computer Vision Laboratory Department of Electrical Engineering Indian Institute of Technology Madras Chennai India

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A New Technique for Hand Gesture Recognition

A New Technique for Hand Gesture Recognition

引用

IEEE International Conference on Image processing

作者： E. Stergiopoulou N. Papamarkos Department of Electrical & Computer Engineering Democritus University of Thrace Xanthi Greece Image Processing and Multimedia Laboratory Greece

A new method for hand gesture recognition is proposed which is based on an innovative self-growing and self-organized neural gas (SGONG) network. Initially, the region of the hand is detected by using a color segmentation technique that depends on a skin-color distribution map. Then, the SGONG network is applied on the segmented hand so as to approach its topology. Based on the output grid of neurons, palm geometric characteristics are obtained which in accordance with powerful finger features allow the identification of the raised fingers. Finally, the hand gesture recognition is accomplished through a probability-based classification method.

关键词： Image segmentation Skin Fingers Chromium Image recognition Image analysis Neural networks Application software computer vision Hidden Markov models

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Automated Hardware-in-the-Loop Modeling and Simulation in Active Sensor Imaging Using T16713 DSP Units

Automated Hardware-in-the-Loop Modeling and Simulation in Ac...

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Ana B. Ramirez Domingo Rodriguez Automated Information Processing Laboratory Electrical and Computer Engineering Department University of Puerto Rico Mayaguez Puerto Rico

This paper presents a new methodology for the modeling and simulation of active sensor imaging systems using a hardware-in-the-loop technique based on TI6713 digital signal processor (DSP) units. The methodology centers on procedures to enhance the degree of automation in the modeling and simulation processes by taking the following actions: (1) improving the automated development of algorithms to compute the two dimensional (2D) discrete Fourier transform (DFT), (2) enhancing the use of 2D DFT algorithms in implementing active sensor image formation operations, and (3) estimating the ambiguity function as the impulse response function of active imaging systems using principles of time-frequency signal representation theory. These actions have produced significant results such as a 30% to 90% improvement in 2D DFT implementations over conventional techniques, enhancement on scalable techniques for computing the ambiguity function, fast implementation techniques for computing image formation operations using the 2D fast Fourier transform (FFT), and integrated MATLABcopy user's interfaces for the overall modeling and simulation processes.

关键词： Image sensors Digital signal processing Mathematical model Discrete Fourier transforms Computational modeling Sensor systems Signal processing algorithms computer interfaces Digital signal processors Automation

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Multiresolution Object Recognition Using Dual Heuristic Programming

Multiresolution Object Recognition Using Dual Heuristic Prog...

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International Joint Conference on Neural Networks (IJCNN)

作者： F. Siddiqui K.M. Iftekharuddin Intelligent Systems and Image Processing Laboratory Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

We present automatic target recognition (ATR) model based on principles of biological vision systems. The model employs reinforcement learning (RL) through Dual Heuristic Programming (DHP). The performance of the reported ATR model is compared to that of our previously reported ATR model, based on Heuristic Dynamic Programming (HDP). The HDP and DHP, known as the Adaptive Critic Designs (ACD), are neural network based implementation of Dynamic Programming (DP). The simulation shows promising results for both HDP and DHP based ATR model in presence of resolution distortion in incoming images and confirms that the DHP model is faster and more robust for our ATR system than the HDP.

关键词： Object recognition Learning Robustness Biological system modeling Machine vision Target recognition Dynamic programming Neural networks Image resolution Nonlinear distortion

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Expression compensation for face recognition using a polar geodesic representation

Expression compensation for face recognition using a polar g...

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3rd International Symposium on 3D Data processing, Visualization, and Transmission, 3DPVT 2006

作者： Mpiperis, Iordanis Malassiotis, Souris Strintzis, Michael G. Information Processing Laboratory Electrical and Computer Engineering Department Aristotle University of Thessaloniki Thessaloniki 541 24 Greece Informatics and Telematics Institute Centre for Research and Technology Hellas 1st Km Thermi-Panorama Rd Thessaloniki 57001 Greece

ISBN: (纸本)0769528252

This paper addresses the problem of face recognition in the presence of facial deformations caused by expressions. An isometric mapping between surfaces is assumed, which allows preservation of geodesic distance between facial points. Subject to this assumption, we propose a novel technique which integrates 2D and 3D information to establish a new deformation invariant representation of the face. The 3D surface is used to define a polar geodesic coordinate space which is independent of the intrinsic geometry of the face. The corresponding color image is embedded in this space and serves as the recognition data. A preceding stage of hierarchical diffeomorphic grid-based image warping before the recognition process combined with a lip segmentation technique are also employed to increase the overall performance of the algorithm. © 2006 IEEE.

关键词： Face recognition

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Intercarrier Interference Analysis for Wireless OFDM in Mobile Channels

Intercarrier Interference Analysis for Wireless OFDM in Mobi...

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2006 IEEE Wireless Communications and Networking Conference (WCNC 2006), vol.4

作者： Xiaozhou Huang Hsiao-Chun Wu Communications and Signal Processing Laboratory Electrical and Computer Engineering Department Louisiana State University Baton Rouge LA USA

Orthogonal Frequency Division Multiplexing (OFDM) employs a set of subcarriers for the information symbol transmission in parallel via the multipath fading channels. Due to its spectral efficiency and robustness over multipath channels, OFDM has been adopted for broadband communications. However, for high-speed mobility, the time-varying channels pose a performance limitation to the wireless OFDM systems. In this paper, we investigate the OFDM system performance in the time-varying channels where the intercarrier interference (ICI) occurs;we study the impacts of the time-varying multipath fadings together with the multiple Doppler spreads. According to our analysis and simulation results, the maximum OFDM symbol normalized Doppler frequency must be less than 0.04 to achieve the signal-to-interference ratio (SIR)=20dB or larger. As the maximum OFDM symbol normalized Doppler frequency increases, the OFDM system performance degrades dramatically. Different irreducible symbol error rate (SER) floors about 10{sup}(-2) for QPSK-OFDM schemes and 10{sup}(-1) for 16QAM-OFDM schemes would arise in case that the maximum OFDM symbol normalized Doppler frequency is fixed at 0.06.

关键词： OFDM ICI Multiple Doppler frequencies Mobile channels Symbol error rate

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Robust Automatic Modulation Classification Using Cumulant Features in the Presence of Fading Channels

Robust Automatic Modulation Classification Using Cumulant Fe...

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2006 IEEE Wireless Communications and Networking Conference (WCNC 2006), vol.4

作者： Songnan Xi Hsiao-Chun Wu Communications and Signal Processing Laboratory Department of Electrical and Computer Engineering Louisiana State University Baton Rouge LA USA

Automatic modulation classification (AMC) is a scheme to automatically identify the modulation types of the transmitted signals by observing the received data samples in the presence of noise and fading channels. Nowadays, AMC plays an important role in both cooperative and non-cooperative communication applications. Very often, multipath fading channels result in the severe AMC performance degradation or induce large classification errors. The negative impacts of multipath fading channels on AMC have been discussed in the existing literature but no solution has ever been proposed so far to the best of our knowledge. In this paper, we propose a new robust AMC algorithm, which applies higher-order statistics (HOS) in a generic framework for blind channel estimation and pattern recognition. The advantage of our new algorithm is that, by carefully designing the essential features needed for AMC, we don't really have to acquire the complete channel information and therefore it can be feasible without any a priori information in practice. The Monte Carlo simulation results show that our new AMC algorithm can achieve the much better classification accuracy than the existing AMC techniques.

关键词： AMC Modulation classification Blind channel estimation Cumulants Fading channels

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Learning Individual Skills and Team Behaviors for Distributed Object Pushing

Learning Individual Skills and Team Behaviors for Distribute...

引用

IEEE International Conference on Mechatronics and Automation

作者： Hossein Aminaiee Majid Nili Ahmadabadi Control and Intelligent Processing Center of Excellence Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper we discuss a learning approach to distributed object pushing. In the proposed approach, first the required individual skills for single-robot object pushing are learned using a fuzzy reinforcement learning method. Then, the robots learn how to coordinate their actions to push the object to the desired configuration cooperatively in a distributed manner. The proposed team-level learning benefits from the knowledge, which is in the form of a Q-table, that the agent has gained in its individual learning phase by a special design of reward signal and state-action representation. Each robot learns a threshold on its Q-value using a single state reinforcement learning method and pushes the object when the Q-value of its best action in the current state is above this threshold. The reward signal is designed based on the robots' Q-tables and no external critic is needed for learning cooperation. Simulation results show that the robots learn their individual skills and a cooperation protocol to push the object cooperatively

关键词： Robot kinematics Learning Protocols Robot control Robotics and automation Intelligent robots Signal design Mechatronics Process control Intelligent control

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Analysis of P300 Classifiers in Brain computer Interface Speller

Analysis of P300 Classifiers in Brain Computer Interface Spe...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： H. Mirghasemi R. Fazel-Rezai M. B. Shamsollahi BDP laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran Brain Image and Signal Processing BISP Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

In this paper, the performance of five classifiers in P300 speller paradigm are compared. Theses classifiers are Linear Support Vector Machine (LSVM), Gaussian Support Vector Machine (GSVM), Neural Network (NN), Fisher Linear Discriminant (FLD), and Kernel Fisher Discriminant (KFD). In classification of P300 waves, there has been a trend to use SVM classifiers. Although they have shown a good performance, in this paper, it is shown that the FLD classifiers outperform the SVM classifiers. FLD classifier uses only ten channels of the recorded electroencephalogram (EEG) signals. This makes them a very good candidate for real-time applications. In addition, FLD approach does not need any optimization similar to other methods. In addition, in this paper, it is shown that the efficiency of using Principal Component Analysis (PCA) for feature reduction results in decreasing the time for the classification and increasing the accuracy

关键词： Brain computer interfaces Electroencephalography Support vector machines Support vector machine classification Principal component analysis Band pass filters Digital filters computer interfaces Cities and towns USA Councils

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