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检索条件"主题词=Algorithm development"

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Advances in Barkhausen Noise Analysis

Advances in Barkhausen Noise Analysis

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Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems

作者： Meyendorf, Norbert Hillmann, Susanne Cikalova, Ulana Schreiber, Juergen Fraunhofer Inst Nondestruct Testing IZFP Dresden Branch Dresden Germany

ISBN: (纸本)9780819499875

The magnetic Barkhausen Noise technique is a well suited method for the characterization of ferromagnetic materials. The Barkhausen effect results in an interaction between the magnetic structure and the microstructure of materials, and is sensitive to the stresses and microstructure related mechanical properties. Barkhausen noise is a complex signal that provides a large amount of information, for example frequency spectrum, amplitude, RMS value, dependence of magnetic field strength, magnetization frequency and fractal behavior. Although this technique has a lot potentials, it is not commonly used in nondestructive material testing. Large sensors and complex calibration procedures made the method impractical for many applications. However, research has progressed in recent years;new sensor designs were developed and evaluated, new algorithms to simplify the calibration and measurement procedures were developed as well as analysis of additional material properties have been introduced.

关键词： Magnetism Sensors Calibration Interference (communication) Nondestructive evaluation Electrodes Magnetic sensors algorithm development Ferromagnetics Analytical research

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Singular wavefront reconstruction with the tilts measured by Shack-Hartmann sensor - art. no. 63463J

Singular wavefront reconstruction with the tilts measured by...

引用

16th International Symposium on Gas Flow, Chemical Lasers, and High-Power Lasers

作者： Aksenov, Valerii Izmallov, Igor Kanev, Feodor Starikov, Feodor Inst Atmospher Opt SB RAS Tomsk Russia

ISBN: (纸本)9780819464309

In the present report the possibility of singular points detections using a Shack-Hartmann sensor is described and the precision of the developed detection algorithm is estimated. Also the algorithms of a singular wave front reconstruction are analyzed. Two algorithms are considered and their properties compared. One of them was developed by D. Fried, its description was found in literature. The second algorithm was developed by authors of the report. The both algorithms were introduced into the software of the sensor and insured satisfactory quality of singular phase reconstruction. The precision of algorithms compared in numerical investigations as well in real laboratory experiments.

关键词： Reconstruction algorithms algorithm development Spiral phase plates Wavefront reconstruction Sensors Wavefronts Wavefront sensors Optical vortices Detection and tracking algorithms Singular optics

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Vessel Filtering of Photoacoustic Images

Vessel Filtering of Photoacoustic Images

引用

Conference on Photons Plus Ultrasound - Imaging and Sensing

作者： Oruganti, Tanmayi Laufer, Jan G. Treeby, Bradley E. UCL Dept Med Phys & Bioengn Gower St London WC1E 6BT England Australian Natl Univ Res Sch Engn Canberra ACT 0200 Australia Charite Julius Wolff Inst D-13353 Berlin Germany

ISBN: (纸本)9780819493507

This paper investigates the application of the vessel filter proposed by Frangi et al.,[MICCAI, LNCS vol. 1496, pp. 130-137, 1998] to photoacoustic images of the vasculature. The filter works by classifying the eigenvalue decomposition of the local Hessian matrix at each image voxel to find tubular structures in the image. A detailed analysis of the algorithm is provided, and the effect of the filters on photoacoustic images is studied using numerical and experimental phantoms. In particular, the impact of the filter on image resolution, feature preservation, and noise is discussed. The vessel filter is then applied to photoacoustic images of the vasculature in mice. The classical Hessian filter is shown to be highly effective at removing noise and highlighting vessels, at the expense of reducing the sharpness of vessel edges.

关键词： Photoacoustic spectroscopy Image filtering 3D image processing Image segmentation Convolution Signal to noise ratio algorithm development Interference (communication) Blood Image analysis

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A General Purpose Adaptive Approach to Image Classification, Automatic Target Detection and Recognition for Multispectral Imagery

A General Purpose Adaptive Approach to Image Classification,...

引用

Conference on Automatic Target Recognition XIX

作者： Cheng, Beato T. Goodrich ISR Syst Chelmsford MA 01824 USA

ISBN: (纸本)9780819476012

Automatic target detection and recognition (ATD/ATR) can be considered one of the most sought after goals in image exploitation. There are no shortage of "good" algorithms in ATD/ATR on paper, yet the problem remains that an algorithm cannot be applied directly to different scenario and expect a similar success rate. One can attribute the difficulties in ATD/ATR to the ambiguity of the definition of "target", and the specific choice of image data and parameters in the design of the algorithms. We propose a general purpose approach to the problem in that we do not specify what a target is, except that it will be chosen by a user from a number of detected anomalies at the end of the classification cycle. At this time, a user can specify a number of attributes to be associated with a candidate target. There is a learning phase where the algorithm and the discriminating parameters are tuned based on the characteristics of the image data and the classification methods. There are a number of attributes associated with a target, both in spectral and spatial values, which can be set by a user. The number of bands used for input can be varied;however it is limited to three to seven bands at this point. Target recognition is achieved when a target candidate has a passing figure of merit, which again is defined by the user. It is hoped that this approach can provide a framework of ATD/ATR with greatest flexibility in algorithm re-use.

关键词： Target recognition Detection and tracking algorithms Target detection Image classification Image processing algorithm development Image segmentation Automatic target recognition Multispectral imaging Reflectivity

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Neural network retrieval of atmospheric temperature and moisture profiles from AIRS/AMSU data in the presence of clouds

Neural network retrieval of atmospheric temperature and mois...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII

作者： Blackwell, William J. Chen, Frederick W. MIT Lincoln Lab 244 Wood St Lexington MA 02173 USA

ISBN: (纸本)0819462896

A nonlinear stochastic method for the retrieval of atmospheric temperature and moisture profiles has been developed and evaluated with sounding data from the Atmospheric InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU), and is presently being adapted for use with the NPOESS Cross-track Infrared Microwave Sounding Suite (CrIMSS) consisting of the hyperspectral Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). The algorithm is implemented in three stages, motivating the name, SCENE (Stochastic Cloud clearing,(1) followed by Eigenvector radiance compression and denoising, followed by Neural network Estimation). First, the infrared radiance perturbations due to clouds are estimated and corrected by combined processing of the infrared and microwave data. Second, a Projected Principal Components (PPC) transform(2) is used to reduce the dimensionality of and optimally extract geophysical profile information from the cloud-cleared infrared radiance data. Third, an artificial feedforward neural network is used to estimate the desired geophysical parameters from the projected principal components. This paper has two major components. First, details of the SCENE algorithm are discussed, including both the architectural implementation and parameter selection and optimization. Second, the performance of the SCENE algorithm is compared with that of the AIRS Level 2 algorithm (version 4.0.9)(3) currently being used for the Aqua mission. The stochastic cloud-clearing algorithm estimates infrared radiances that would be observed in the absence of clouds. This algorithm examines 3x3 sets of nine AIRS fields of view, selects the clearest ones, and then in a series of simple linear-and non-linear operations on both the infrared and microwave channels estimates a single cloud-cleared infrared spectrum for the 3x3 set. The algorithm is both trained and tested using global numerical weather analyses within 60 degrees of the eq

关键词： Neural networks Infrared radiation Clouds Microwave radiation Stochastic processes Evolutionary algorithms algorithm development Sensors Cadmium Radiative transfer

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PARALLEL IMPLEMENTATION OF SOME FAST ADAPTIVE algorithmS ON A DIGITAL SIGNAL PROCESSOR (DSP) NETWORK

PARALLEL IMPLEMENTATION OF SOME FAST ADAPTIVE ALGORITHMS ON ...

引用

CONF ON ADVANCED SIGNAL PROCESSING algorithmS, ARCHITECTURES, AND IMPLEMENTATIONS 2

作者： REYNAUD, R CHEBIRA, A DEMOMENT, G Univ. de Paris-Sud (France)

ISBN: (纸本)0819406945

Several important problems in signal processing, such as linear prediction, linear regression, or spectrum factorization, need close-to-Toeplitz matrices to be factored. To solve these problems, several fast algorithms have been derived. They differ by the kind of adaptivity (block processing or exponential weighting of the data) and by the kind of recursion (order or time recursion), but they all have a common vector ladder recursion, involving an hyperbolic rotation. These algorithms are therefore well suited for implementation on an array processor. But there exists a number of applications where an efficient parallel implementation of these algorithms on a DSP network would be very attractive. The redundancy suppression, which is performed in the equations to get a fast algorithm, destroys the processing regularity of the corresponding standard algorithms, which prevents efficient high level parallel implementation. Auxiliary quantities, such as generalized reflections coefficients, are introduced that don't have the same dimensions as primary quantities. As a result there is a loss of efficiency in such tasks processing, and this leads to use array partitioning in as many sub-arrays as the number of DSPs available. If the number m of DSPs is low compared to primary quantities of dimension p (m << p/m) (i.e. a low level parallelism) and if the dimension a of reflection coefficients is also low ((alpha) << p/m), the global efficiency of a parallel implementation on a DSP network may still be interesting, with in addition, the advantages associated to such a network : simple design, simple control. To illustrate this, an application of the method to a Fast Recursive Least Squares algorithm is presented.

关键词： Digital signal processing Signal processing Data modeling algorithm development Array processing Filtering (signal processing) Scattering Digital filtering Matrices Network architectures

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Automated detection of nodules attached to the pleural and mediastinal surface in low-dose CT scans - art. no. 69150X

Automated detection of nodules attached to the pleural and m...

引用

Medical Imaging 2008 Conference

作者： van Ginneken, Bram Tan, Andre Murphy, Keelin de Hoop, Bart-Jan Prokop, Mathias Univ Med Ctr Utrecht Image Sci Inst Utrecht Netherlands

ISBN: (纸本)9780819470997

This paper presents a new computer-aided detection scheme for lung nodules attached to the pleural or mediastinal surface in low dose CT scans. First the lungs are automatically segmented and smoothed. Any connected set of voxels attached to the wall - with each voxel above minus 500 HU and the total object within a specified volume range - was considered a candidate finding. For each candidate, a refined segmentation was computed using morphological operators to remove attached structures;For each candidate, 35 features were defined, based on their position in the lung and relative to other structures, and the shape and density within and around each candidate. In a training procedure an optimal set of 15 features was determined with a k-nearest-neighbor classifier and sequential floating forward feature selection. The algorithm was trained with a data set of 708 scans from a lung cancer screening study containing 224 pleural nodules and tested on an independent test set of 226 scans from the same program with 58 pleural nodules. The algorithm achieved a sensitivity of 52% with an average of 0.76 false positives per scan. At 2.5 false positive marks per scan, the sensitivity increased to 80%.

关键词： Lung Image segmentation Computed tomography Lung cancer algorithm development Blood vessels Computer aided diagnosis and therapy Cancer Computer aided design Spherical lenses

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Sensitivity of hilbert magnitude and phase to structural damage

Sensitivity of hilbert magnitude and phase to structural dam...

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Smart Structures and Materials 2003 Conference

作者： Pines, D Salvino, L Univ Maryland Alfred Gessow Rotorcraft Ctr Smart Struct Lab College Pk MD 20742 USA

ISBN: (纸本)0819448613

This paper discusses a new signal-processing tool involving the use of empirical mode decomposition and its application to health monitoring of structures. Empirical mode decomposition is a time series analysis method that extracts a custom set of basis sets to describe the vibratory response of a system. In conjunction with the Hilbert Transform, the empirical mode decomposition method provides some unique information about the nature of the vibratory response. In this paper, the Hilbert phase for discrete one-dimensional structural elements is compared to the phase obtained from the use of dereverberated wave mechanics. Simulation results indicate that the Hilbert phase is proportional to mass and stiffness properties between two successive degrees of freedom. Hence, the Hilbert phase can be used to infer, locate and possibly quantify the amount of damage in a structure.

关键词： Diagnostics Wave propagation Sensors Signal analyzers Time series analysis Wave mechanics Aerospace engineering algorithm development Environmental sensing Smart structures

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High aspect ratio depth determination using non-destructive AFM

High aspect ratio depth determination using non-destructive ...

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Conference on Metrology, Inspection, and Process Control for Microlithography XIII

作者： Jaiprakash, VC Lagus, ME Meyyappan, A Muckenhirn, S Siemens Mciroelect Inc Hopewell Junction NY 12533 USA

ISBN: (纸本)0819431516

ULSI processing for the manufacture of devices such as DRAMs involves fabrication of several high aspect ratio structures. The determination and control of depth of these structures is crucial for device performance. We report the utilization of Atomic Force Microscopy to characterize 0.2 mu m ground rule products. Features with 2.1 mu m depth and 0.2 mu m top nominal top width dimensions can be consistently measured. To accomplish this a recently developed Deep Trench (DT) scan mode is employed and used in conjunction with new Super Angle Tapered CD (SATCD) and Super Angle Cone (SAC) tips. New analysis algorithms are developed to extract the data in a repeatable form with decreased sensitivity to changes in tip size (initial quality), tip shape (wear), and sample (process shift).

关键词： Critical dimension metrology Atomic force microscopy Nondestructive evaluation Process control algorithm development Manufacturing Semiconducting wafers Pattern recognition Metrology Microelectronics

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ANOMALY DETECTION IN DATA USING NEURAL NETWORKS WITH NATURAL-SELECTION

ANOMALY DETECTION IN DATA USING NEURAL NETWORKS WITH NATURAL...

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1ST CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS

作者： DESSERT, PE Carnegie Group Inc. (United States)

ISBN: (纸本)0819408751

Frequently, time series data taken off machines contains erroneous data points due to errors in the measurement of the data. One such instance of measuring devices recording anomalies occurs in the `crash testing' of vehicles. In this task, senors are placed on the vehicle and the `crash dummy' and the vehicle is then crashed into a barrier. Force and acceleration data is collected which an engineer inspects for anomalies, correcting those that are found. Artificial neural network (ANN) technology was successfully applied to this problem to eliminate the cost and delay of this manual process. To apply ANN technology in this domain, two technical problems needed to be resolved; the appropriate network architecture and the size of the input set. These two issues are quite common and must be addressed in the development of any neural network application. To resolve both issues, I employed a machine learning algorithm that simulates the Darwinian concept of `survival of the fittest' known as the genetic learning algorithm (GLA). By combining the strength of the GLA and ANNs, a network architecture was created that `optimized' the size, speed, and accuracy of the ANN. This `hybridized' system also used the GLA to determine the `smallest' number of inputs into the ANN that were necessary to detect anomalies in data. This algorithm is known as GENENET, and is described in this paper.

关键词： Neural networks Genetics Neurons Artificial neural networks Network architectures Genetic algorithms Evolutionary algorithms algorithm development Sensors Measurement devices

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