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检索条件"主题词=Algorithm development"

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APPLICATION OF NEURAL NETWORKS TO HYPERSPECTRAL IMAGE-ANALYSIS AND INTERPRETATION 3

APPLICATION OF NEURAL NETWORKS TO HYPERSPECTRAL IMAGE-ANALYS...

引用

3RD ANNUAL INTERNATIONAL CONF ON APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS

作者： SHEN, SS HORBLIT, BD Lockheed Palo Alto Research Lab. (United States)

ISBN: (纸本)0819408743

The newest airborne and spaceborne imaging sensors, unlike their predecessors, generate data at tens to hundreds of wavelengths simultaneously. The advent of these imaging spectrometers greatly increases the detail of the information available to the analyst, but the concomitant disadvantages of vastly increased data volume and complexity have stimulated the search for more efficient and accurate hyperspectral data exploitation techniques. This paper describes two neural network models used in conjunction to analyze hyper-spectral image data. The first neural network is based on an unsupervised backward error propagation model. This network generates without supervision low dimensional discriminant feature vectors from the original high dimensional signals. These features are analyzed by the second neural network, which is a layered feed-forward neural network based on statistical principles, namely Parzen window density estimation and Bayes decision rule. This network estimates class-conditional probability density functions using training samples and classifies data points so that the expected risk is minimized. Results of applying these two neural networks to 210-band AVIRIS data are presented.

关键词： Neural networks Image analysis Data modeling Statistical analysis Artificial neural networks Spectral resolution Absorption algorithm development Hyperspectral imaging Spectrometers

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PREDICTIVE NOSEPOINTING AND FLIGHTPATH DISPLAYS FOR AIR-TO-AIR COMBAT 3

PREDICTIVE NOSEPOINTING AND FLIGHTPATH DISPLAYS FOR AIR-TO-A...

引用

CONF ON HELMET-MOUNTED DISPLAYS 3

作者： VIKEN, SA BURLEY, JR Lockheed Engineering and Sciences Co. (United States) NASA Langley Research Ctr. (United States)

ISBN: (纸本)0819408603

As part of the High-Angle-of-Attack Technology Program (HATP), two integrated pictorial displays have been developed for piloted simulation evaluations and, ultimately, for flight testing on board the F/A-18 High Alpha Research Vehicle (HARV). The first concept is a nosepointing display which illustrates the range of control the pilot has over the aircraft nose. The second concept is a predictive flightpath display that allows the pilot to see how his current control inputs will affect his aircraft's future position and orientation. The development of both display concepts will be discussed, as well as the results from a piloted simulation experiment in which pilots viewed the flightpath display in a wide-field-of-view Helmet-Mounted Display (HMD) while engaged in an air-combat situation.

关键词： Fourier transforms Head-mounted displays Visualization Data modeling algorithm development Heads up displays Optical spheres Device simulation Nose Weapons

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SPECIFICATION AND CONTROL OF BEHAVIORAL ROBOT PROGRAMS

SPECIFICATION AND CONTROL OF BEHAVIORAL ROBOT PROGRAMS

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SENSOR FUSION CONF : CONTROL PARADIGMS AND DATA STRUCTURES

作者： KAHN, P Advanced Decision Systems (United States)

ISBN: (纸本)0819407488

Behavioral robotics is the specification and control of robots as a composition, coordination, and adaptation of more primitive sub-behaviors. The past decade has led to the development of many useful algorithms that can support valuable behavioral function in robots (e.g., perception, robotics, planning, domain rules). Increased availability of these component algorithms increases the need for robot control methods that can select between gross behaviors in addition to providing control within a given behavior. For example, gross behavioral changes may consider when and whether to attend to new stimuli, and if and how that stimuli can lead to new or different behaviors. This paper describes an approach being developed for the specification and control of these types of behavioral programs. The first section introduces a task oriented approach to behavioral robot program specification and control. The second section then describes a Behavioral Architecture for Robot Tasks (BART) being developed. A BART language is being built to provide a portable tool to support various robot programming and execution strategies, evidence accrual methods, and domain representations. This language is being used to develop behavioral programs that control tanks and tank platoons.

关键词： Foam Control systems Information operations algorithm development Computer programming Robotics Sensor fusion Composites Nanoimprint lithography Sensors

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INTELLIGENT VISUAL CONTROL FOR A FLEXIBLE INSPECTION CELL

INTELLIGENT VISUAL CONTROL FOR A FLEXIBLE INSPECTION CELL

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CONF ON MACHINE VISION ARCHITECTURES, INTEGRATION, AND APPLICATIONS

作者： BATCHELOR, BG Univ. of Wales College of Cardiff (United Kingdom)

ISBN: (纸本)0819407526

The flexible inspection cell consists of an (X,Y,(theta) )-table surrounded by a set of computer controlled lamps. Several cameras are placed around the cell and a pick-and-place manipulator is able to put objects onto the table and/or remove them from it. The physical organization of the cell and the architecture of the system controller are both described. The latter consists of a set of up to eight slave image processing modules, whose actions are organized by a Prolog program. The system provides a convenient user interface, with the following features: pull-down menus, pop-up menus, on-line HELP, cursor (for investigation of image features), interactive mode (for algorithm development), pre-recorded speech output, and speech recognition (for working in hands-off mode). The flexible inspection cell provides a general purpose facility for inspecting complex objects, small-batch artifacts, and assemblies of components.

关键词： Inspection Optical inspection Visualization algorithm development Cameras Control systems Human-machine interfaces Image processing Lamps Speech recognition

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INDUCTIVE LEARNING USING GENERALIZED DISTANCE MEASURES

INDUCTIVE LEARNING USING GENERALIZED DISTANCE MEASURES

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CONF ON ADAPTIVE AND LEARNING SYSTEMS

作者： HONAVAR, V Iowa State Univ. (United States)

ISBN: (纸本)0819408719

This paper briefly reviews the two currently dominant paradigms in machine learning--the connectionist network (CN) models and symbol processing (SP) systems; argues for the centrality of knowledge representation frameworks in learning; examines a range of representations in increasing order of complexity and measures of similarity or distance that are appropriate for each of them; introduces the notion of a generalized distance measure (GDM) and presents a class of GDM-based inductive learning algorithms (GDML). GDML are motivated by the need for an integration of symbol processing (SP) and connectionist network (CN) approaches to machine learning. GDM offer a natural generalization of the notion of distance or measure of mismatch used in a variety of pattern recognition techniques (e.g., k-nearest neighbor classifiers, neural networks using radial basis functions, and so on) to a range of structured representations such strings, trees, pyramids, association nets, conceptual graphs, etc. which include those used in computer vision and syntactic approaches to pattern recognition. GDML are a natural extension of generative or constructive learning algorithms for neural networks that enable an adaptive and parsimonious determination of the network topology as well as the desired weights as a function of learning Applications of GDML include tasks such as planning, concept learning, and 2- and 3-dimensional object recognition. GDML offer a basis for a natural integration of SP and CN approaches to the construction of intelligent systems that perceive, learn, and act.

关键词： Distance measurement Surface plasmons Machine learning Detection and tracking algorithms Intelligence systems Evolutionary algorithms Object recognition Pattern recognition algorithm development Neural networks

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FEEDFORWARD NEURAL NETS AND ONE-DIMENSIONAL REPRESENTATION

FEEDFORWARD NEURAL NETS AND ONE-DIMENSIONAL REPRESENTATION

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1ST CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS

作者： DIXON, LCW MILLS, DJ Hatfield Polytechnic (United Kingdom)

ISBN: (纸本)0819408751

Feedforward nets can be trained to represent any continuous function, and training is equivalent to solving a nonlinear optimization problem. Unfortunately, it frequently leads to an error function with a Hessian matrix that is effectively singular at the solution. Traditional quadratic based optimization algorithms do not perform superlinearly on functions with a singular Hessian, but results on univariate functions show that even so they are more efficient and reliable than backpropagation. A feedforward net is used to represent a superposition of its own sigmoid activation function. The results identify some conditions for which the Hessian of the error function is effectively singular.

关键词： Artificial neural networks Neural networks Superposition algorithm development Data hiding Brain Complex systems Detection and tracking algorithms Neurons Tolerancing

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NEURAL STRUCTURES IN DIGITAL HALF-TONING

NEURAL STRUCTURES IN DIGITAL HALF-TONING

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CONF ON OPTICAL COMPUTING AND NEURAL NETWORKS ( PREPRINTS )

作者： TUTTASS, T BROJA, M BRYNGDAHL, O Univ. Essen (Germany)

ISBN: (纸本)0819410128

Neural nets present various possibilities for local and global processing in digital halftoning. For global processing the Hopfield-type network was examined for its usage. The constraints concerning this model are presented and their effects for the binarization problem are shown. The numerical description leads to a basic parallelism to the well known iterative Fourier transform algorithm (IFTA), applied in digital halftoning.

关键词： Fourier transforms Neural networks Computing systems Neurons Optical computing Binary data algorithm development algorithms Visual system Physics

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CORNER DETECTION USING SPLINE-WAVELETS 2

CORNER DETECTION USING SPLINE-WAVELETS

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CONF ON CURVES AND SURFACES IN COMPUTER VISION AND GRAPHICS 2

作者： CHAN, AK CHUI, CK ZHA, J LIU, Q Texas A&M Univ. (United States)

ISBN: (纸本)081940747X

Detection of corners in an image is very useful in computer vision and pattern recognition. The existing algorithms for corner detection seem to be insufficient in many situations. The corner detection algorithm proposed in this paper is based on spline-wavelet decompositions. Corner and edge detectors are constructed from the 2-D wavelet transform coefficients. A somewhat sophisticated thresholding technique is applied to remove noise and minor irregularities in the images. Noise can be further reduced if additional processing is applied to the component images at all resolutions. Information on the edges and corners is contained in the component images in all the octaves to facilitate precise localization. A real-time wavelet decomposition algorithm is developed for the corner and edge detectors. It is very efficient and requires very little memory, since most of the computations involve only simple moving average operations and sub-sampling.

关键词： Corner detection Wavelets Detection and tracking algorithms Sensors Computer vision technology Machine vision Wavelet transforms algorithm development Computer graphics Visualization

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NEW ASSIGNMENT algorithmS FOR DATA ASSOCIATION

NEW ASSIGNMENT ALGORITHMS FOR DATA ASSOCIATION

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4TH CONF ON THE SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1992

作者： CASTANON, DA Boston Univ. (United States)

ISBN: (纸本)0819408638

This paper presents an overview of new classes of algorithms for the algorithm concepts for the solution of combinatorial optimization problems arising in data association. These algorithms are based on extensions of Bertsekas' auction algorithm. The paper includes experimental results using these algorithms and a modification of the algorithm of Jonker and Volgenant on 2-dimensional measurement-track data association problems in the presence of false alarms, missed detections, sensor bias noise, and sensor measurement noise. The results indicate that some of the new algorithms are very efficient for the solution of these data association problems.

关键词： Detection and tracking algorithms algorithm development Sensors Data processing Signal processing Data modeling algorithms Information operations Optimization (mathematics) Radon

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PARALLEL AND ADAPTIVE HIGH-RESOLUTION DIRECTION FINDING

PARALLEL AND ADAPTIVE HIGH-RESOLUTION DIRECTION FINDING

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CONF ON ADVANCED SIGNAL PROCESSING algorithmS, ARCHITECTURES, AND IMPLEMENTATIONS 3

作者： VANPOUCKE, F MOONEN, M DEPRETTERE, E Katholieke Univ. Leuven (Belgium) Delft Univ. of Technology (Netherlands)

ISBN: (纸本)081940943X

The direction-of-arrival (DOA) estimation problem consists in determining the angles of arrival of a number of signals impinging on a sensor array. Recently, the so-called ESPRIT method of Roy and Paulraj has received a great deal of attention in the literature. The method employs matrix decomposition techniques, such as singular value decomposition (SVD) and generalized Schur decomposition (GSD). The computational complexity thus involved represents a serious impediment, especially when a real-time implementation is aimed for. Therefore, the aim here is to develop an ESPRIT-type algorithm which is fully adaptive and amenable to parallel implementation. By introducing adaptivity, the computational complexity per sampling period is reduced from (Omicron) (m³) to (Omicron) (m²), where m is the `problem size,' i.e., the number of antenna doublets. On a parallel processor array with (Omicron) (m²) processors, the throughput is then (Omicron) (m^o), which means that the number of measurements that are processed per time unit is independent of the problem size. The algorithm is based on an adaptive SVD updating algorithm, combined with an adaptive GSD. The corresponding systolic implementation is based on the systolic SVD updating array of Moonen et al.

关键词： Matrices Sensors algorithm development Interference (communication) Array processing Antennas Data processing Parallel computing Electrical engineering Phase shifts

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