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algorithmICA 2001年第3期31卷 442-457页

作者： Smythe, RT Wellner, J Oregon State Univ Dept Stat Corvallis OR 97331 USA Univ Washington Dept Stat Seattle WA 98195 USA

We analyze the Shell Sort algorithm under the usual random permutation model. Using empirical distribution functions, we recover Louchard's result that the running time of the 1-stage of (2, 1)-Shell Sort has a limiting distribution given by the area under the absolute Brownian bridge. The analysis extends to (h, 1)Shell Sort where we find a limiting distribution given by the sum of areas under correlated absolute Brownian bridges. A variation of (h, 1)-Shell Sort which is slightly more efficient is presented and its asymptotic behavior analyzed.

关键词： empirical distribution functions Brownian bridge sorting algorithm random permutation model asymptotic distribution

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On automatic cloud detection over ocean

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2001年第15期22卷 3047-3052页

作者： Kärner, O Di Girolamo, L Tartu Astrophys Observ EE-61602 Toravere Estonia Univ Illinois Urbana IL 61801 USA

An automatic cloud classification algorithm is proposed for the Advanced Very High Resolution Radiometer (AVHRR), based on a 5-D histogram technique. The technique determines three-level (high, medium, low) cloud amount and the average cloud-top brightness temperature (BT) and reflectance for 128 x 128 pixel areas. Comparison of the products for NOAA-11 AVHRR measurements during 14 orbits over oceans with the International Satellite Cloud Classification Project DX products for the same AVHRR data set is presented.

关键词： oceans Reflectance international satellite sorting algorithm

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Approximating the limiting quicksort distribution

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RANDOM STRUCTURES & algorithmS 2001年第3-4期19卷 376-406页

作者： Fill, JA Janson, S Johns Hopkins Univ Dept Math Sci Baltimore MD 21218 USA Univ Uppsala Dept Math S-75105 Uppsala Sweden

The limiting distribution of the normalized number of comparisons used by Quicksort to sort an array of n numbers is known to be the unique fixed point with zero mean of a certain distributional transformation S. We study the convergence to the limiting distribution of the sequence of distributions obtained by iterating the transformation S. beginning with a (nearly) arbitrary starting distribution. We demonstrate geometrically fast convergence for various metrics and discuss some implications for numerical calculations of the limiting Quicksort distribution. Finally, we give companion lower bounds which show that the convergence is not faster than geometric. (C) 2001 John Wiley & Sons, Inc.

关键词： quicksort characteristic function density moment generating function sorting algorithm coupling Fourier analysis Kolmogorov-Smirnov distance total variation distance integral equation numerical analysis d(p)-metric

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Design patterns for sorting 01

Design patterns for sorting

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32nd SIGCSE Technical Symposium on Computer Science Education

作者： Nguyen, D Wong, SB Rice Univ Dept Comp Sci Houston TX 77251 USA

ISBN: (纸本)1581133294

Drawing on Merritt's divide-and-conquer sorting taxonomy [1], we model comparison-based sorting as an abstract class with a template method to perform the sort by relegating the splitting and joining of arrays to its concrete subclasses. Comparison on objects is carried out via an abstract ordering strategy. This reduces code complexity and simplifies the analyses of the various concrete sorting algorithms. Performance measurements and visualizations can be added without modifying any code by utilizing the decorator design pattern. This object-oriented design not only provides the student a concrete way of unifying seemingly disparate sorting algorithms but also help him/her differentiate them at the proper level of abstraction.

关键词： design pattern sorting programs sorting algorithm template process grade level of abstraction Visualization Concrete drawing Drawing encoding complexity ordering strategy Painters

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Characterization of North American land cover from NOAA-AVHRR data using the EOS MODIS land cover classification algorithm

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GEOPHYSICAL RESEARCH LETTERS 2000年第7期27卷 977-980页

作者： Friedl, MA Muchoney, D McIver, D Gao, F Hodges, JCF Strahler, AH Boston Univ Dept Geog Boston MA 02215 USA Boston Univ Ctr Remote Sensing Boston MA 02215 USA

Land cover is a key boundary condition in weather, climate, and terrestrial biogeochemical models. Until recently, such models have used maps depicting potential vegetation, which are known to be of relatively poor quality, to parameterize land surface properties. In this paper we describe the compilation and assessment of a new map of North American land cover produced through the application of advanced pattern recognition techniques to multitemporal satellite data. This map was produced in a fully automated fashion using supervised classification methods that are robust, fully automated, and repeatable. The processing flow described in this paper is a prototype of the algorithm to be used to generate maps of global land cover using data from EOS MODIS. The superior quality and timeliness of these maps should be very useful for a wide array of sub-continental to global-scale modeling and analysis activities.

关键词： maps sorting algorithm land cover Moderate Resolution Imaging Spectroradiometer pictorial pattern recognition algorithm Classification Methods Collected papers

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Monitoring Great Lakes ice cover with satellite synthetic aperture radar (SAR)

Monitoring Great Lakes ice cover with satellite synthetic ap...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Leshkevich, GA Nghiem, SV Kwok, R NOAA Great Lakes Environm Res Lab Ann Arbor MI 48105 USA

ISBN: (纸本)0780363590

During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes ice types using the Jet Propulsion Laboratory (JPL) C-band scatterometer, together with surface-based ice physical characterization measurements and environmental parameters were acquired concurrently with RADARSAT and ERS-2 SAR data. Using a supervised classification algorithm, measured backscatter values (converted to dB) for three ice types and calm water were applied to an 8 x 8 pixel averaged ERS-2 calibrated SAR image. Certain assumptions were made on the local incidence angle, one of which was that any change in incidence angle across a distributed target was neglected, i.e. a distributed target corresponds to one average value of the incidence angle (23 degrees was used). Although the calculated overall uncertainty was about +/- 1 dB as a result of the averaging and incidence angle effect, an algorithm to correct for power loss and local incidence angle effect is applied in this study to the ERS-2 image, resulting in a more accurate classification.

关键词： angle of incidence Synthetic aperture radar Ice Types sorting algorithm stagnant area RADARSAT Ice Cover decibel Great Lakes power loss environmental parameters mean value winter season averaging

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Synthetic aperture radar (SAR) image segmentation using a new modified fuzzy c-means algorithm

Synthetic aperture radar (SAR) image segmentation using a ne...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Chumsamrong, W Thitimajshima, P Rangsanseri, Y King Mongkuts Inst Technol Ladkrabang Fac Engn Dept Telecommun Engn Bangkok 10520 Thailand

ISBN: (纸本)0780363590

Generally fuzzy c-means algorithm is one proved that very well suited for remote sensing image segmentation. exhibited sensitivity to the initial guess with regard to both speed and stability. But it also showed sensitivity to noise. This paper proposes a fully automatic technique to obtain image clusters. A modified fuzzy c-means classification algorithm is used to provide a fuzzy partition. This method is less sensitive to noise as it filters the image while clustering it, which is based on the consideration of the neighbors as factors the attract pixels into their cluster, The experimental results on JERS-1 Synthetic Aperture Radar (SAR) image demonstrate its potential usefulness.

关键词： Synthetic aperture radar image segmentation fuzzy partition sorting algorithm Fuzzy Image JERS

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Structure selection in synthetic aperture radar scattering models 25

Structure selection in synthetic aperture radar scattering m...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Akyildiz, Y Moses, RL Ohio State Univ Dept Elect Engn Columbus OH 43210 USA

ISBN: (纸本)0780362934

High-frequency models for radar backscatter can include components with different structures that correspond to different physical scattering mechanisms on an object. We consider the problem of structure selection for an attributed scattering center model that includes both localized and distributed scattering terms. We propose three structure classification algorithms, and compare their performance. We show that a threshold test on the estimated length parameter performs as well as a GLRT test, but is computationally more efficient. A computationally fast image-based test is shown to perform as well as the GLRT and length-based tests for scattering center lengths greater than twice the crossrange resolution of the measurements.

关键词： broadcasting Radar Backscatter Synthetic aperture radar High frequency sorting algorithm WELLS

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Multitime frequency classifiers for neighboring modulations in a multiplivative noise environment 25

Multitime frequency classifiers for neighboring modulations ...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Gelle, G Colas, M Delaunay, G URCA LAM F-51687 Reims 02 France

ISBN: (纸本)0780362934

This communication presents two new classification algorithms based on Time Varying Higher Order Statistic (TVHOS). These two algorithms benefit from the advantageous localization properties provided by TVHOS4 for instantaneous frequency laws disrupted by a multiplicative noise. The classification scheme used is a bank of several normalized TVHOS4 correlators. Simulations illustrate successful performance of the classification algorithms for different situations and especially if the SNR is higher than -7 dB.

关键词： multiplicative noise noise environment sorting algorithm classification scheme Classifiers Higher order statistics instantaneous frequency

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A New Approximate Maximal Margin Classification algorithm 00

A New Approximate Maximal Margin Classification Algorithm

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Annual Conference on Neural Information Processing Systems

作者： Claudio Gentile DSI Universita' di Milano Via Comelico 39 20135 Milano Italy

ISBN: (纸本)0262122413

A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. Norm p ≥ 2 for a set of linearly separable data. Our algorithm, called ALMA_p (Approximate Large Margin algorithm w.r.t. Norm p), takes O ((p-1) X~2/α~2γ~2) corrections to separate the data with p-norm margin larger than (1 ― α) γ, where γ is the p-norm margin of the data and X is a bound on the p-norm of the instances. ALMA_p avoids quadratic (or higher-order) programming methods. It is very easy to implement and is as fast as on-line algorithms, such as Rosenblatt's perceptron. We report on some experiments comparing ALMA_p to two incremental algorithms: Perceptron and Li and Long's ROMMA. Our algorithm seems to perform quite better than both. The accuracy levels achieved by ALMA_p are slightly inferior to those obtained by Support vector Machines (SVMs). On the other hand, ALMA_p is quite faster and easier to implement than standard SVMs training algorithms.

关键词： algorithms Tumor margin status Fasting sorting algorithm Neural Networks (Computer) Lithium Approximate Maximal

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