Extrapolation

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






Conferences related to Extrapolation

Back to Top

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

    TBA

  • 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

Back to Top

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.




Xplore Articles related to Extrapolation

Back to Top

Preliminary design of high temperature lithium-lead blanket with SiC cooling panel

M. Ichinose; Y. Yamamoto; K. Noborio; Y. Takeuchi; S. Konishi 2009 23rd IEEE/NPSS Symposium on Fusion Engineering, 2009

A high temperature lithium-lead blanket, which can be made within a limited extrapolations of present technology, has been proposed. The blanket structure is based on F82H as vessel material, and Pb-17Li as breeder. SiCf/SiC cooling panel is inserted between them to achieve high temperature extraction of Pb- 17Li while maintaining F82H under allowable temperature limit. Neutronic analysis using ANISN code ...


Cardiac risk assessment based on QTc speculation and trending from past references

Thomas Ho Chee Tat; Chen Xiang 2011 Computing in Cardiology, 2011

A method to construct a predictive time series index based on QTc-intervals is proposed in this paper. Monitored electrocardiography (ECG) data is converted into a root mean square of successive difference (RMSSD) trend-line by first finding the QT intervals [1] and then using [2]. The trend-line is then used as a priori in extrapolating the predictive trend. The next unknown ...


Direct far-field GO synthesis of single-reflector antennas using the extrapolation technique

C. S. Lee Antennas and Propagation Society International Symposium, 1989. AP-S. Digest, 1989

The application of an extrapolation technique developed by the author (1987) to the direct GO (geometrical optics) synthesis of single-reflector antennas is described. The technique is simple and easily applicable to an arbitrary beam shape. The technique is basically similar to that of dual-reflector shaping, except that only the amplitude of the far field is satisfied within the GO approximation. ...


Distributed adaptive compressed video sensing using smoothed projected landweber reconstruction

Li Ran; Gan Zongliang; Cui Ziguan; Wu Minghu; Zhu Xiuchang China Communications, 2013

A novel Compressed-Sensing-based (CS-based) Distributed Video Coding (DVC) system, called Distributed Adaptive Compressed Video Sensing (DISACOS), is proposed in this paper. In this system, the input frames are divided into key frames and non-key frames, which are encoded by block CS sampling. The key frames are encoded as CS measurements at substantially higher rates than the non-key frames and decoded ...


Learning one-counter languages in polynomial time

Piotr Berman; Robert Roos Foundations of Computer Science, 1987., 28th Annual Symposium on, 1987

We demonstrate that the class of languages accepted by deterministic one- counter machines, or DOCAs (a natural subset of the context-free languages), is learnable in polynomial time. Our learning protocol is based upon Angluin's concept of a "minimally adequate teacher" who can answer membership queries about a concept and provide counterexamples to incorrect hypothesized concepts. We also demonstrate that the ...


More Xplore Articles

Educational Resources on Extrapolation

Back to Top

eLearning

Preliminary design of high temperature lithium-lead blanket with SiC cooling panel

M. Ichinose; Y. Yamamoto; K. Noborio; Y. Takeuchi; S. Konishi 2009 23rd IEEE/NPSS Symposium on Fusion Engineering, 2009

A high temperature lithium-lead blanket, which can be made within a limited extrapolations of present technology, has been proposed. The blanket structure is based on F82H as vessel material, and Pb-17Li as breeder. SiCf/SiC cooling panel is inserted between them to achieve high temperature extraction of Pb- 17Li while maintaining F82H under allowable temperature limit. Neutronic analysis using ANISN code ...


Cardiac risk assessment based on QTc speculation and trending from past references

Thomas Ho Chee Tat; Chen Xiang 2011 Computing in Cardiology, 2011

A method to construct a predictive time series index based on QTc-intervals is proposed in this paper. Monitored electrocardiography (ECG) data is converted into a root mean square of successive difference (RMSSD) trend-line by first finding the QT intervals [1] and then using [2]. The trend-line is then used as a priori in extrapolating the predictive trend. The next unknown ...


Direct far-field GO synthesis of single-reflector antennas using the extrapolation technique

C. S. Lee Antennas and Propagation Society International Symposium, 1989. AP-S. Digest, 1989

The application of an extrapolation technique developed by the author (1987) to the direct GO (geometrical optics) synthesis of single-reflector antennas is described. The technique is simple and easily applicable to an arbitrary beam shape. The technique is basically similar to that of dual-reflector shaping, except that only the amplitude of the far field is satisfied within the GO approximation. ...


Distributed adaptive compressed video sensing using smoothed projected landweber reconstruction

Li Ran; Gan Zongliang; Cui Ziguan; Wu Minghu; Zhu Xiuchang China Communications, 2013

A novel Compressed-Sensing-based (CS-based) Distributed Video Coding (DVC) system, called Distributed Adaptive Compressed Video Sensing (DISACOS), is proposed in this paper. In this system, the input frames are divided into key frames and non-key frames, which are encoded by block CS sampling. The key frames are encoded as CS measurements at substantially higher rates than the non-key frames and decoded ...


Learning one-counter languages in polynomial time

Piotr Berman; Robert Roos Foundations of Computer Science, 1987., 28th Annual Symposium on, 1987

We demonstrate that the class of languages accepted by deterministic one- counter machines, or DOCAs (a natural subset of the context-free languages), is learnable in polynomial time. Our learning protocol is based upon Angluin's concept of a "minimally adequate teacher" who can answer membership queries about a concept and provide counterexamples to incorrect hypothesized concepts. We also demonstrate that the ...


More eLearning Resources

IEEE-USA E-Books

  • 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."

  • 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.

  • Front Matter

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

  • 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.

  • 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

  • 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

  • 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

  • Constrained Reconstruction

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

  • 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



Standards related to Extrapolation

Back to Top

No standards are currently tagged "Extrapolation"


Jobs related to Extrapolation

Back to Top