Extrapolation

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In mathematics, extrapolation is the process of constructing new data points . (Wikipedia.org)






Conferences related to Extrapolation

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ICASSP 2017 - 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


2013 IEEE 77th Vehicular Technology Conference (VTC Spring)

VTC will bring together individuals from academia, industry and government to discuss and exchange ideas in the fields of mobile, wireless and vehicular technology as well as the applications and services associated with such technology. Features include world-class plenary speakers, panel sessions, tutorials, and both technical and application-based sessions.


2012 IEEE 12th International Conference on Data Mining (ICDM)

ICDM has established itself as the world's premier research conference in data mining covering all aspects of data mining in a wide range related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing.

  • 2011 IEEE 11th International Conference on Data Mining (ICDM)

    The conference provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences. It covers all aspects of data mining and draws researchers and application developers from a wide range of data mining related areas.

  • 2010 IEEE 10th International Conference on Data Mining (ICDM)

    The IEEE International Conference on Data Mining (ICDM) has established itself as the world's premier research conference in data mining. The 10th edition of ICDM (ICDM '10) provides a leading forum for presentation of original research results, as well as exchange and dissemination of innovative,practical development experiences. The conference covers all aspects of data mining, including algorithms, software and systems, and applications

  • 2009 IEEE International Conference on Data Mining (ICDM)

    The conference covers all aspects of data mining, including algorithms, software and systems, and applications. In addition, ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing.

  • 2008 IEEE International Conference on Data Mining (ICDM)

    Conference covers all aspects of data mining,algorithms,software & systems, and applications.ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing.

  • 2007 IEEE International Conference on Data Mining (ICDM)

  • 2006 IEEE International Conference on Data Mining (ICDM)


2012 IEEE 13th International Conference on Information Reuse & Integration (IRI)

Given volumes of information in digital form, we are constantly faced with new challenges with regards to efficiently using it and extracting useful knowledge from it. Information reuse and integration (IRI) seeks to maximally exploit such available information to create new knowledge and to reuse it for addressing newer challenges. It plays a pivotal role in the capture, maintenance, integration, validation, extrapolation, and application of knowledge to augment human decision -making capabilities.

  • 2011 IEEE International Conference on Information Reuse & Integration (IRI)

    Given volumes of information in digital form, we are constantly faced with new challenges with regards to efficiently using it and extracting useful knowledge from it. Information reuse and integration (IRI) seeks to maximally exploit such available information to create new knowledge and to reuse it for addressing newer challenges. It plays a pivotal role in the capture, maintenance, integration, validation, extrapolation, and application of knowledge to augment human decision -making capabilities.

  • 2010 IEEE International Conference on Information Reuse & Integration (2010 IRI)

    Given volumes of information in digital form, we are constantly faced with new challenges with regards to efficiently using it and extracting useful knowledge from it. Information reuse and integration (IRI) seeks to maximally exploit such available information to create new knowledge and to reuse it for addressing newer challenges. It plays a pivotal role in the capture, maintenance, integration, validation, extrapolation, and application of knowledge to augment human decision -making capabilities.

  • 2009 IEEE International Conference on Information Reuse & Integration (2009 IRI)

    Given volumes of information in digital form, we are constantly faced with new challenges with regards to efficiently using it and extracting useful knowledge from it. Information reuse and integration (IRI) seeks to maximally exploit such available information to create new knowledge and to reuse it for addressing newer challenges. It plays a pivotal role in the capture, maintenance, integration, validation, extrapolation, and application of knowledge to augment human decision-making capabilities in variou

  • 2008 IEEE International Conference on Information Reuse & Integration (2008 IRI)

    The increasing volumes and dimensions of information dramatically impact on effective decision-making. To remedy this situation, Information Reuse and Integration (IRI) seeks to maximize the reuse of information by creating simple, rich, and reusable knowledge representations and consequently explore strategies for integrating this knowledge into legacy systems. IRI plays a pivotal role to capture, represent, maintain, integrate, validate, extrapolate, and apply both information and knowledge for enhancing

  • 2007 IEEE International Conference on Information Reuse & Integration (2007 IRI)

    Given volumes of information in digital form, we are constantly faced with new challenges with regards to efficiently using it and extracting useful knowledge from it. Information reuse and integration (IRI) seeks to maximally exploit such available information to create new knowledge and to reuse it for addressing newer challenges. It plays a pivotal role in the capture, maintenance, integration, validation, extrapolation, and application of knowledge to augment human decision-making.


2010 4th International Conference on Intelligent Information Technology Application (IITA)

IITA 2010 provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in any aspects of intelligent information technology

  • 2009 Third International Symposium on Intelligent Information Technology Application (IITA)

    IITA 2009 provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in any aspects of intelligent information technology. This year, we especially encourage papers on machine learning, signal Processing, communication Systems, circuits and Systems etc. We also welcome papers that highlight successful modern applications of Intelligent Information Technology, such as Multimedia ,Bioinformatics, Power, Neural Systems, Control and so on



Periodicals related to Extrapolation

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Industry Applications Magazine, IEEE

This magazine publishes articles concerning technical subjects and professional activities that are within the scope of IAS and are of interest to society members. The information includes but is not limited to articles, product reviews, book reviews, new standards, education information, announcements of conferences, workshops, new publications, committee meetings and reports of IAS activities.


Nuclear Science, IEEE Transactions on

All aspects of the theory and applications of nuclear science and engineering, including instrumentation for the detection and measurement of ionizing radiation; particle accelerators and their controls; nuclear medicine and its application; effects of radiation on materials, components, and systems; reactor instrumentation and controls; and measurement of radiation in space.


Reliability, IEEE Transactions on

Principles and practices of reliability, maintainability, and product liability pertaining to electrical and electronic equipment.


Signal Processing Letters, IEEE

Rapid dissemination of new results in signal processing world-wide.


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Xplore Articles related to Extrapolation

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Spectrum estimation of time series with missing data

H. Dante ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1985

In several practical situations involving the estimation of sinusoids from time series, the data available is not complete due to missing data points. The Gerschberg-Papoulis extrapolation algorithm, originally used for the extrapolation of band-limited signals is used for the estimation of the spectrum from incomplete time series. The use of this algorithm is studied for cases where the spectrum of ...


A computational model for simulating spatial aspects of crime in urban environments

P. L. Brantingham; U. Glasser; B. Kinney; K. Singh; M. Vajihollahi 2005 IEEE International Conference on Systems, Man and Cybernetics, 2005

In this paper, we present a novel approach to computational modeling of social systems. By combining the abstract state machine (ASM) formalism with the multi-agent modeling paradigm, we obtain a formal semantic framework for modeling and integration of established theories of crime analysis and prediction. We focus here on spatial and temporal aspects of crime in urban areas. Our work ...


Two fast extrapolation/superresolution algorithms

P. J. S. G. Ferreira Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2000

We propose two fast algorithms for the extrapolation of band-limited images (or, equivalently, for spectrum extrapolation of finite support objects). The algorithms are noniterative and based on the Cholesky decomposition of certain Hermitian positive-definite matrices. One of the algorithms is based on a image domain formulation of the problem, whereas the other is based on the dual frequency domain formulation. ...


On the properties of continuants and sensitivity computations

Y. Ceyhun IEEE Transactions on Circuit Theory, 1973

Properties of continuants under differentiation are investigated and closed- form formulas are obtained for the differentiation of the ratio of two continuants with respect to an independent parameter. These results are applied to the sensitivity analysis of ladder-type as well as certain nonladder-type structures.


Large-Area Deterministic Simulation of Natural Runoff from Snowmelt Based on Landsat MSS Data

Michael F. Baumgartner; Jaroslav Martinec; Klaus Seidel IEEE Transactions on Geoscience and Remote Sensing, 1986

This work sentnow a method of periodic evaluation of snow-covered areas by digital processing of Landsat data. Since the s cover was mapped for the first time in a large and morphologicomplex alpine basin, it was necessary to develop procedures to determine the snow coverage for partly clouded regions or for incomplete satellite scenes. The changing areal extent of the ...


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Educational Resources on Extrapolation

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eLearning

Spectrum estimation of time series with missing data

H. Dante ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1985

In several practical situations involving the estimation of sinusoids from time series, the data available is not complete due to missing data points. The Gerschberg-Papoulis extrapolation algorithm, originally used for the extrapolation of band-limited signals is used for the estimation of the spectrum from incomplete time series. The use of this algorithm is studied for cases where the spectrum of ...


A computational model for simulating spatial aspects of crime in urban environments

P. L. Brantingham; U. Glasser; B. Kinney; K. Singh; M. Vajihollahi 2005 IEEE International Conference on Systems, Man and Cybernetics, 2005

In this paper, we present a novel approach to computational modeling of social systems. By combining the abstract state machine (ASM) formalism with the multi-agent modeling paradigm, we obtain a formal semantic framework for modeling and integration of established theories of crime analysis and prediction. We focus here on spatial and temporal aspects of crime in urban areas. Our work ...


Two fast extrapolation/superresolution algorithms

P. J. S. G. Ferreira Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2000

We propose two fast algorithms for the extrapolation of band-limited images (or, equivalently, for spectrum extrapolation of finite support objects). The algorithms are noniterative and based on the Cholesky decomposition of certain Hermitian positive-definite matrices. One of the algorithms is based on a image domain formulation of the problem, whereas the other is based on the dual frequency domain formulation. ...


On the properties of continuants and sensitivity computations

Y. Ceyhun IEEE Transactions on Circuit Theory, 1973

Properties of continuants under differentiation are investigated and closed- form formulas are obtained for the differentiation of the ratio of two continuants with respect to an independent parameter. These results are applied to the sensitivity analysis of ladder-type as well as certain nonladder-type structures.


Large-Area Deterministic Simulation of Natural Runoff from Snowmelt Based on Landsat MSS Data

Michael F. Baumgartner; Jaroslav Martinec; Klaus Seidel IEEE Transactions on Geoscience and Remote Sensing, 1986

This work sentnow a method of periodic evaluation of snow-covered areas by digital processing of Landsat data. Since the s cover was mapped for the first time in a large and morphologicomplex alpine basin, it was necessary to develop procedures to determine the snow coverage for partly clouded regions or for incomplete satellite scenes. The changing areal extent of the ...


More eLearning Resources

IEEE-USA E-Books

  • A Heuristic Exposition of Wiener's Mathematical Theory of Prediction and Filtering

    This chapter contains sections titled: 1 The Auto-correlation Function, 2 The Integral Equation, 3 The Modified Integral Equation, 4 The Factorization Problem, 5 The Functions ψ1, ψ2, and α, 6 The Prediction Operator

  • Back Matter

    It has been the opinion of many that Wiener will be remembered for his Extrapolation long after Cybernetics is forgotten. Indeed few computer-science students would know today what cybernetics is all about, while every communication student knows what Wiener's filter is. The work was circulated as a classified memorandum in 1942, as it was connected with sensitive war- time efforts to improve radar communication. This book became the basis for modern communication theory, by a scientist considered one of the founders of the field of artifical intelligence. Combining ideas from statistics and time- series analysis, Wiener used Gauss's method of shaping the characteristic of a detector to allow for the maximal recognition of signals in the presence of noise. This method came to be known as the "Wiener filter."

  • Front Matter

    This chapter contains sections titled: Title, Copyright, Preface, Contents

  • Miscellaneous Problems Encompassed by the Technique of this Book

    This chapter contains sections titled: 5.0 The Problem of Approximate Differentiation, 5.1 An Example of Approximate Differentiation, 5.2 A Misleading Example of Approximate Differentiation, 5.3 Interpolation and Extrapolation

  • Resume of Fundamental Mathematical Notions

    This chapter contains sections titled: 1.00 Fourier Series, 1.01 Orthogonal Functions, 1.02 The Fourier Integral, 1.04 More on the Fourier Integral; Realizability of Filters, 1.1 Generalized Harmonic Analysis, 1.18 Discrete Arrays and Their Spectra, 1.2 Multiple Harmonic Analysis and Coherency Matrices, 1.3 Smoothing Problems, 1.4 Ergodic Theory, 1.5 Brownian Motion, 1.6 Poisson Distributions, 1.7 Harmonic Analysis in the Complex Domain

  • Constrained Reconstruction

    This chapter contains sections titled: Half-Fourier Reconstruction Extrapolation-Based Reconstruction Parametric Reconstruction Methods Appendix This chapter contains sections titled: Exercises

  • Effects of Melting on Faulting and Continental Deformation

    The presence of melt is closely related to the localization of deformation in faults and shear zones in a variety of tectonic settings. This relationship is observed on length scales from the outcrop to plate boundary faults to orogens. However, the question of whether melting induces localization, or localization creates a pathway for melts, can rarely be answered from field observations alone. Experimental studies show that rock strength decreases exponentially with increasing volume percentage of melt. This suggests that melting facilitates strain localization where deformation would be homogeneous in the absence of melt. Yet, the extrapolation of experimental relationships between rock strength and melt content to natural conditions at depth in the lithosphere remains speculative, largely because the grain-scale processes underlying dramatic weakening at small amounts of melt have yet to be investigated in crustal rocks. New geochronological methods for dating minerals that crystallized during deformation in the presence of melt have the potential to constrain the time lag between the onset of melting and deformation in naturally deformed anatectic rocks. An indirect, but clear answer to the question of whether melting induces strain localization on a regional scale comes from numerical models of orogenesis which can be run in the presence or absence of low-viscosity domains that approximate the mechanical behavior of partially melted rock. These models show that melting induces lateral flow of anatectic crust within horizontal channels usually situated at the base of the continental crust. These channels have strong vertical strain gradients, especially at their boundaries where shear zones accommodate lateral extrusion of the anatectic rock in between. Together with their bounding shear zones, these flow channels form a new class of faults, which we term " ;extrusional faults." Extrusional faults containing long-lived melt (tens of millions of years) can support large, broadly distributed topographic loads such as orogenic plateaus and can exhume deeply buried rocks from beneath orogens. In contrast, strike-slip and oblique-slip faults serve as steep conduits for the rapid ascent, differentiation, and crystallization of melt. The relatively short residence time of melts in such moderately to steeply dipping fault systems can lead to episodic motion, with long periods of creep punctuated by shorter periods of melt veining, magmatic activity, and/or faster slip.

  • Analysis of Mobility Protocols for Multimedia

    This chapter provides comprehensive analysis of several generations of mobility protocols (e.g., 1G, 2G, 3G, and 4G) in order to extrapolate the common abstract functions during a mobility event. It describes how discovery, configuration, authentication, security association, and media routing functions associated with a mobile's handoff are performed for each of the cellular and IP-based mobility protocols and then maps the respective network parameters for these mobility protocols to each of the common mobility functions. A comparative analysis and extrapolation of the abstract primitives can help to design an optimized mobility system with a given resource constraints and build the optimization mechanisms for each these mobility functions.

  • Practical Aspects of Active Automata Learning

    This chapter contains sections titled: Introduction Regular Extrapolation Challenges in Regular Extrapolation Interacting with Real Systems Membership Queries Reset Parameters and Value Domains The NGLL Conclusion and Perspectives References

  • The Wiener RMS (Root Mean Square) Error Criterion in Filter Design and Prediction

    This chapter contains sections titled: 1 Linear Filters, 2 Minimization of RMS Error, 3 Determination of the Weighting Function, 4 Realization of Operator-- Mathematical Formulation, 5 RC Filter, 6 Prediction and Lag with and without Noise



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