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.

  • ICASSP 2015 - 2015 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.

  • ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

    ICASSP 2014 will be the world s largest and most comprehensive technical conference focused on the many facets of signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and oral/poster sessions on the most up-to-date topics in signal processing research.

  • ICASSP 2013 - 2013 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.

  • ICASSP 2012 - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing

    The latest research results on both theories and applications on signal processing will be presented and discussed among participants from all over the world. Video/Speech Signal processing used in human interface between Robots and Personal users will be highlighted.

  • ICASSP 2011 - 2011 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 on: Audio and electroacoustics Bio imaging and signal processing Design and implementation of signal processing systems Image and multidimensional signal processing Industry technology tracks Information forensics and security.

  • ICASSP 2010 - 2010 IEEE International Conference on Acoustics, Speech and Signal Processing

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  • ICASSP 2009 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing

    The 34th ICASSP will be held in Taiwan April 19-24, 2009. 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.

  • ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing


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.


Signal Processing Letters, IEEE

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


Signal Processing, IEEE Transactions on

The technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital, electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of thesetechnologies.



Most published Xplore authors for Extrapolation

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Xplore Articles related to Extrapolation

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The dolphin dieoff: long-term effects and recovery of the population

G. P. Scott; D. M. Burn; L. J. Hansen OCEANS '88. A Partnership of Marine Interests. Proceedings, 1988

First Page of the Article ![](/xploreAssets/images/absImages/00794905.png)


The Toy Language Syndrome

B. K. Rosen IEEE Transactions on Software Engineering, 1978

Theorists and implementers can easily interact in such a way that software performs improperly, even if there are no mathematical mistakes in the theory and no coding bugs in the implementation. This correspondence explains the problem and some ways to cope with it. Examples are drawn from program proving, language design, and code optimization.


A frequency-aspect extrapolation algorithm for ISAR image simulation based on two-dimensional ESPRIT

Yuanxun Wang; Hao Ling IEEE Transactions on Geoscience and Remote Sensing, 2000

A frequency-aspect extrapolation algorithm is proposed to accelerate ISAR image simulation using fast multipole solvers. A two-dimensional (2D) multiple-arrival model based on high-frequency physics is proposed to parameterize the induced currents on the target. A 2D estimation of parameters via rotation invariance technique (ESPRIT) algorithm is developed to estimate the model parameters from a limited number of computed data samples ...


Simulation of Broadband Microwave Oscillations in the Gunn-Diode Sources Involving Impact Ionization

E. D. Prokhorov; D. V. Pavlenko 2006 International Conference on Mathematical Methods in Electromagnetic Theory, 2006

The model for numerical simulation of the Gunn diode with electric field strength sufficient for the development of the impact ionization in the moving high-field domains is described and some results are presented. The form of the current oscillations and frequency spectra is in good agreement with experimentally measured data. It is shown that the Gunn diode operating under conditions ...


Effects of the increase of side erase band width on off-track capability of high frequency magnetic recording

Mingjyue Huang; Derek Yeo; Tuan Tran IEEE Transactions on Magnetics, 1996

Method of measuring side erase band width with a spinstand has been improved using narrow-band overwrite filter read-back track profile, which provides a sharp vertex and two straight side lines. The resultant measurements are in good agreement with those obtained from `747' tests. Effects of the increase of the side erase band width caused from high frequency magnetic recording has ...


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Educational Resources on Extrapolation

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eLearning

The dolphin dieoff: long-term effects and recovery of the population

G. P. Scott; D. M. Burn; L. J. Hansen OCEANS '88. A Partnership of Marine Interests. Proceedings, 1988

First Page of the Article ![](/xploreAssets/images/absImages/00794905.png)


The Toy Language Syndrome

B. K. Rosen IEEE Transactions on Software Engineering, 1978

Theorists and implementers can easily interact in such a way that software performs improperly, even if there are no mathematical mistakes in the theory and no coding bugs in the implementation. This correspondence explains the problem and some ways to cope with it. Examples are drawn from program proving, language design, and code optimization.


A frequency-aspect extrapolation algorithm for ISAR image simulation based on two-dimensional ESPRIT

Yuanxun Wang; Hao Ling IEEE Transactions on Geoscience and Remote Sensing, 2000

A frequency-aspect extrapolation algorithm is proposed to accelerate ISAR image simulation using fast multipole solvers. A two-dimensional (2D) multiple-arrival model based on high-frequency physics is proposed to parameterize the induced currents on the target. A 2D estimation of parameters via rotation invariance technique (ESPRIT) algorithm is developed to estimate the model parameters from a limited number of computed data samples ...


Simulation of Broadband Microwave Oscillations in the Gunn-Diode Sources Involving Impact Ionization

E. D. Prokhorov; D. V. Pavlenko 2006 International Conference on Mathematical Methods in Electromagnetic Theory, 2006

The model for numerical simulation of the Gunn diode with electric field strength sufficient for the development of the impact ionization in the moving high-field domains is described and some results are presented. The form of the current oscillations and frequency spectra is in good agreement with experimentally measured data. It is shown that the Gunn diode operating under conditions ...


Effects of the increase of side erase band width on off-track capability of high frequency magnetic recording

Mingjyue Huang; Derek Yeo; Tuan Tran IEEE Transactions on Magnetics, 1996

Method of measuring side erase band width with a spinstand has been improved using narrow-band overwrite filter read-back track profile, which provides a sharp vertex and two straight side lines. The resultant measurements are in good agreement with those obtained from `747' tests. Effects of the increase of the side erase band width caused from high frequency magnetic recording has ...


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IEEE-USA E-Books

  • Introduction

    This chapter contains sections titled: 0.1 The Purpose of This Book, 0.2 Time Series, 0.3 Communication Engineering, 0.4 Techniques of Time Series and Communication Engineering Contrasted, 0.41 The Ensemble, 0.42 Correlation, 0.43 The Periodogram, 0.44 Operational Calculus, 0.45 The Fourier Integral; Need of the Complex Plane, 0.5 Time Series and Communication Engineering--The Synthesis, 0.51 Prediction, 0.52 Filtering, 0.53 Policy Problems, 0.6 Permissible Operators: Translation Group in Time, 0.61 Past and Future, 0.62 Subclasses of Operators, 0.7 Norms and Minimization, 0.71 The Calculus of Variations, 0.8 Ergodic Theory, 0.81 Brownian Motion, 0.9 Summary of Chapters

  • 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

  • The Linear Predictor for a Single Time Series

    This chapter contains sections titled: 2.01 Formulation of the Problem of the Linear Predictor, 2.02 The Minimization Problem, 2.03 The Factorization Problem, 2.04 The Predictor Formula, 2.1 Examples of Prediction, 2.2 A Limiting Example of Prediction, 2.3 The Prediction of Functions Whose Derivatives Possess Auto-correlation Coefficients, 2.4 Spectrum Lines and Non- absolutely Continuous Spectra, 2.5 Prediction by the Linear Combination of Given Operators, 2.6 The Linear Predictor for a Discrete Time Series

  • Index

    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."

  • Table of the Laguerre Functions

    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."

  • The Linear Filter for a Single Time Series

    This chapter contains sections titled: 3.0 Formulation of the General Filter Problem, 3.1 Minimization Problem for Filters, 3.2 The Factorization of the Spectrum, 3.3 Prediction and Filtering, 3.4 The Error of Performance of a Filter; Long-lag Filters, 3.5 Fillers and Ergodic Theory, 3.6 Computation of Specific Filter Characteristics, 3.7 Lagging Filters, 3.8 The Determination of Lag and Number of Meshes in a Filter, 3.9 Detecting Filters for High Noise Level, 3.91 Filters for Pulses, 3.92 Filters Having Characteristics Linearly Dependent on Given Charaderistics, 3.93 Computation of Filter: Resume

  • 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."

  • 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.

  • 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

  • The Linear Predictor and Filter for Multiple Time Series

    This chapter contains sections titled: 4.0 Symbolism and Definitions for Multiple Time Series, 4.1 Minimization Problem for Multiple Time Series, 4.2 Method of Undetermined Coefficients, 4.3 Multiple Prediction, 4.4 Special Cases of Prediction, 4.5 A Discrete Case of Prediction, 4.8 General Tecbnlque of DIscrete Prediction



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