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检索条件"机构=Configurable Computing Lab Department of Electrical and Computer Engineering"

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A real-time occupancy map from multiple video streams

A real-time occupancy map from multiple video streams

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： A. Hoover B.D. Olsen Electrical and Computer Engineering Department Visual Computing Lab University of California San Diego La Jolla CA USA Department of Medical Inform. & Image Analysis Laboratory of Image Analysis University of Aalborg Denmark

We describe an algorithm to fuse intensity data from multiple video cameras to create a spatial-temporal occupancy map. The camera layout is assumed to resemble a security video network. The occupancy map is a two-dimensional raster image, uniformly distributed in the floor-plane. Each map pixel contains a binary value, signifying whether the designated floorspace is empty or occupied. Our algorithm requires only one difference and one look-up table operation to determine each pixel's effect upon the map. This brevity of operations allows the spatial occupancy map to be temporally computed at real-time video rates. We demonstrate our algorithm operating in several dynamic scenarios.

关键词： Streaming media Cameras Signal processing algorithms Fuses Data security Table lookup Image analysis Image processing Biomedical imaging laboratories

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Path planning for mobile robots using a video camera network

Path planning for mobile robots using a video camera network

引用

IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

We describe a novel method to plan paths for mobile robots in an environment observed by a network of video cameras. The multiple video streams are fused to generate a spatial-temporal map of freespace. Updated at 5 Hz, this map concurrently locates both static and dynamic obstacles. Our novel method computes a polynomial-shaped path from current position to goal position for each map update (at 5 Hz), thus accomplishing both path planning and dynamic obstacle avoidance simultaneously. We demonstrate our methods operating in several dynamic scenarios, and compare our methods against paths planned using a numeric potential field.

关键词： Path planning Mobile robots Robot vision systems Cameras Robotics and automation Robot sensing systems computer vision computer networks Polynomials Mechanical sensors

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A scalable VLSI architecture for binary prefix sums

A scalable VLSI architecture for binary prefix sums

引用

International Symposium on Parallel Processing

作者： R. Lin K. Nakano S. Olariu M.C. Pinotti J.L. Schwing A.Y. Zomaya Department of Computer Science SUNY Geneseo Geneseo NY USA Department of Electrical and Computer Engineering Nagoya Institute of Technology Nagoya Japan Department of Computer Science Old Dominion University Norfolk VA USA Parallel Computing Research Lab Department of Electrical and ElectronicEng University of Western Australia Perth Australia

The task of computing binary prefix sums (BPS, for short) arises, for example, in expression evaluation, data and storage compaction, and routing. The paper describes a scalable VLSI architecture for the BPS problem. The authors adopt as the central theme of this effort, the recognition of the fact that the broadcast delay incurred by a signal propagating along a bus is, at best, linear in the distance traversed. Thus, one of the design criteria is to keep buses as short as possible. In this context, the main contribution is to show that one can use short buses in conjunction with shift switching to obtain a scalable VLSI architecture for the BPS problem.

关键词： Very large scale integration Switches Broadcasting Parallel processing computer architecture Propagation delay Communication switching computer science USA Councils Registers

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ASICs, processors, and configurable computing

ASICs, processors, and configurable computing

引用

Annual Hawaii International Conference on System Sciences (HICSS)

作者： B.L. Hutchings Configurable Computing Lab Department of Electrical and Computer Engineering Brigham Young University Provo UT USA

Summary form only given. It is often suggested that configurable computing represents a new computational middle ground that fills the existing void between conventional microprocessors and ASICs. This point of view is based upon the observation that FPGAs share some similarities with both processors and ASICs. FPGAs are seen as similar to processors because they are customized in the field by the end user by downloading configuration data into the device. They can also be seen as similar to ASICs because they can implement high performance, application specific circuits. It is hoped that if configurable computing can be shown to be similar to conventional processors, it will be possible to borrow microprocessor architecture and compilation techniques for use in the configurable computing community.

关键词： Application specific integrated circuits Field programmable gate arrays Microprocessors Amplitude shift keying Performance gain Parallel processing Distributed computing computer architecture computer languages Circuit synthesis

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Randomized reinforcement based scheduling in parallel processor systems

Randomized reinforcement based scheduling in parallel proces...

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Annual Hawaii International Conference on System Sciences (HICSS)

作者： A.Y. Zomaya M. Clements S. Olariu Parallel Computing Research Lab Department of Electrical & Electronic Engineering University of Western Australia Perth Australia Department of Computer Science Old Dominion University Norfolk VA USA

Task scheduling is important for the proper functioning of parallel processor systems. The static scheduling of tasks onto networks of parallel processors is well defined and documented in the literature. However, in many practical situations, a priori information about the tasks that need to be scheduled is not available. In such situations tasks usually arrive dynamically and the scheduling should be performed online or "on the fly". We present a framework based on stochastic reinforcement learning which is usually used to solve optimization problems in a simple and efficient way. The use of reinforcement learning reduces the dynamic scheduling problem to that of learning a stochastic approximation of an unknown average error surface. The learning system develops an association between the best action (schedule) and the current state of the environment (parallel system).

关键词： Processor scheduling Job shop scheduling Optimal scheduling Dynamic scheduling Parallel processing Adaptive scheduling Learning systems Stochastic processes Unsupervised learning Signal processing

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Efficient identification of non-robustly untestable path delay faults

Efficient identification of non-robustly untestable path del...

引用

IEEE International Test Conference

作者： Zhongcheng Li Yinghua Min R.K. Brayton CAD Lab Institute of Computing Technology Chinese Academy and Sciences China Center for Fault Tolerant Computing CAD Laboratory Institute of Computing Technology Chinese Academy and Sciences Beijing China Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA

This paper presents an efficient implication-based approach for identifying non-robustly untestable path delay faults. It starts from possible conflicts to find untestable faults by performing static implication. It is neither path-oriented nor space-search based. Experimental results for ISCAS'85 benchmark circuits demonstrate that a significant portion of non-robustly non-robustly untestable path delay faults is identified efficiently. The method can be combined easily with ATPG-based approaches for path delay testing to yield cost effective methods for path delay faults in large circuits.

关键词： Fault diagnosis Circuit faults Circuit testing Robustness Delay effects electrical fault detection Logic testing Benchmark testing Fault detection Redundancy

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A hierarchical approach for solving large-scale traveling salesman problem

A hierarchical approach for solving large-scale traveling sa...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： D.C. Park A.L. Figueras C. Chen Intelligent Computing Research Lab Department of Electrical and Computer Engineering Florida International University Miami FL USA

A hierarchical approach which combines an unsupervised learning algorithm and a recursive Hopfield neural network is proposed for solving the large-scale traveling salesman problem (TSP). For a TSP with given number of cities, an unsupervised learning algorithm was first used to find the clusters for decomposing the given problem and then a recursive version of the Hopfield network was applied to the centroids of the clusters. The proposed recursive Hopfield network was also applied to cities in each cluster in order to find an optimal path. A final tour was obtained by connecting together the resultant paths of each cluster.< >

关键词： Large-scale systems Traveling salesman problems Cities and towns Neurons Clustering algorithms Temperature Annealing Unsupervised learning Intelligent networks Electronic mail

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Gradient based fuzzy c-means (GBFCM) algorithm

Gradient based fuzzy c-means (GBFCM) algorithm

引用

International Joint Conference on Neural Networks (IJCNN)

作者： D.C. Park I. Dagher Intelligent Computing Research Lab Department of Electrical and Computer Engineering Florida International University Miami FL USA

In this paper, a clustering algorithm based on the fuzzy c-means algorithm (FCM) and the gradient descent method is presented. In the FCM, the minimization process of the objective function is proceeded by solving two equations alternatively in an iterative fashion. Each iteration requires the use of all the data at once. In our proposed approach one datum at a time is presented to the network, and the minimization is proceeded using the gradient descent method. Compared to FCM, the experimental results show that our algorithm is very competitive in terms of speed and stability of convergence for large number of data.< >

关键词： Clustering algorithms Iterative algorithms Minimization methods Equations Convergence Neurons Stability

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Bilinear recurrent neural network

Bilinear recurrent neural network

引用

International Joint Conference on Neural Networks (IJCNN)

作者： D.C. Park Yan Zhu Intelligent Computing Research Lab Department of Electrical and Computer Engineering Florida International University Miami FL USA

A recurrent neural network and its training algorithm are proposed in this paper. Since the proposed algorithm is based on the bilinear polynomial, it can model many nonlinear systems with much more parsimony than the higher order neural networks based on Volterra series. The proposed bilinear recurrent neural network (BLRNN) is compared with multilayer perceptron neural networks (MLPNN) for time series prediction problems. The results show that the BLRNN is robust and outperforms the MLPNN in terms of prediction accuracy.< >

关键词： Recurrent neural networks Neurons Polynomials Neural networks Nonlinear systems Artificial neural networks Feedforward neural networks Intelligent networks computer networks Electronic mail

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Myoelectric signal recognition using fuzzy clustering and artificial neural networks in real time

Myoelectric signal recognition using fuzzy clustering and ar...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： A. Del Boca D.C. Park Intelligent Computing Research Lab Department of Electrical and Computer Engineering Florida International University Miami FL USA

Application of EMG-controlled functional neuromuscular stimulation to a denervated muscle depends largely on the successful discrimination of the myoelectric signal (MES) by which the subject desires to execute control over the impeded movement. This can be achieved by an adaptive and flexible interface that is robust regardless of electrode location, strength of remaining muscle activity or even personal conditions. A real-time application of an artificial neural network that can accurate recognize the MES signature is proposed in this paper. MES features are first extracted through Fourier analysis and clustered using the fuzzy c-means algorithm. Data obtained by this unsupervised learning technique are then automatically targeted and presented to a multilayer perceptron type neural network. For real-time operation, a digital signal processor operates over the resulting set of weights and maps the incoming signal to the stimulus control domain. Results show a highly accurate discrimination of the control signal over interference patterns.< >

关键词： Muscles Artificial neural networks Automatic control Neuromuscular stimulation Impedance Robustness Electrodes Feature extraction Data mining Algorithm design and analysis

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