Interpolation

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In the mathematical field of numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points. (Wikipedia.org)






Conferences related to Interpolation

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2013 Computing in Cardiology Conference (CinC)

Provide a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology.

  • 2012 Computing in Cardiology Conference (CinC)

    Provide a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology.

  • 2011 Computing in Cardiology Conference (CinC)

    Provides a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology.

  • 2010 Computing in Cardiology (CinC)

    Computing in Cardiology (formerly Computers in Cardiology) is one of the premier events focusing on computer applications in clinical cardiology and cardiovascular research. The conference fosters interdisciplinary discussions and collaboration among physicians, engineers, physicists, biologists, computer scientists and others in research and development in Cardiology.

  • 2009 36th Annual Computers in Cardiology Conference (CinC)

    The Computers in Cardiology conference provides an international forum for scientific presentations focusing on computer applications in clinical cardiology and cardiovascular research. The conference fosters interdisciplinary discussions and collaboration between physicians, engineers, physicists, biologists, computer scientists and others engaged in research in this area.


2012 54th International Symposium ELMAR

Image and Video Processing; Multimedia Communications; Speech and Audio Processing; Wireless Commununications; Telecommunications; Antennas and Propagation; e-Learning and m-Learning; Navigation Systems; Ship Electronic Systems; Power Electronics and Automation; Naval Architecture; Sea Ecology.

  • 2011 53rd International Symposium ELMAR

    Image and Video Processing; Multimedia Communications; Speech and Audio Processing; Wireless Commununications; Telecommunications; Antennas and Propagation; e-Learning and m-Learning; Navigation Systems; Ship Electronic Systems; Power Electronics and Automation; Naval Architecture; Sea Ecology

  • 2010 52nd International Symposium ELMAR

    Image and Video Processing; Multimedia Communications; Speech and Audio Processing; Wireless Commununications; Telecommunications; Antennas and Propagation; e -Learning and m-Learning; Navigation Systems; Ship Electronic Systems; Power Electronics and Automation; Naval Architecture; Sea Ecology


2011 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2011)

The scope of the conference includes, but not limited to AI, Artificial Life and Artificial Immune Systems, Cloud Computing, Computer Vision, Data Mining, Fuzzy System, Genetic Algorithms, Information Retrieval, Intelligent Control, Robotics, Machine Learning, Machine Translation, Neural Networks, Rough Set, Systems Biology, Video & Image Processing

  • 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2010)

    AI, Artificial Life and Artificial Immune Systems, Cloud Computing, Computer Vision, Data Mining, Fuzzy System, Genetic Algorithms, Information Retrieval, Intelligent Control, Robotics, Machine Learning, Machine Translation, Neural Networks, Rough Set, Systems Biology, Video & Image Processing, etc.

  • 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009)

    The scope of the conference includes, but not limited to AI, Artificial Life and Artificial Immune Systems, Cloud Computing, Computer Vision, Data Mining, Fuzzy System, Genetic Algorithms, Information Retrieval, Intelligent Control, Robotics, Machine Learning, Machine Translation, Neural Networks, Rough Set, Systems Biology, Video & Image Processing, etc.


2010 6th International Conference on Wireless and Mobile Communications (ICWMC)

The Sixth International Conference on Wireless and Mobile Communications (ICWMC 2010) in Spain follows on the previous events on advanced wireless technologies, wireless networking, and wireless applications.


2010 International Conference on Electrical and Control Engineering (ICECE)

recent advances, new techniques and applications in the field of Electrical Engineering and Automation Control.


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Periodicals related to Interpolation

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Fuzzy Systems, IEEE Transactions on

Theory and application of fuzzy systems with emphasis on engineering systems and scientific applications. (6) (IEEE Guide for Authors) Representative applications areas include:fuzzy estimation, prediction and control; approximate reasoning; intelligent systems design; machine learning; image processing and machine vision;pattern recognition, fuzzy neurocomputing; electronic and photonic implementation; medical computing applications; robotics and motion control; constraint propagation and optimization; civil, chemical and ...


Image Processing, IEEE Transactions on

Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.


Multimedia, IEEE Transactions on

The goal of IEEE Transactions on Multimedia is to integrate all aspects of multimedia systems and technology, signal processing, and applications. It will cover various aspects of research in multimedia technology and applications including, but not limited to: circuits, algorithms and macro/micro-architectures, software, detailed design, synchronization, interaction, joint processing and coordination of multimedia and multimodal signals/data, compression, storage, retrieval, communication, ...


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.


Very Large Scale Integration (VLSI) Systems, IEEE Transactions on

Integrated circuits and systems;VLSI based Architecture and applications; highspeed circuits and interconnect; mixed-signal SoC; speed/area/power/noise tradeoffs in CMOS circuits.



Most published Xplore authors for Interpolation

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Xplore Articles related to Interpolation

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Surface Extraction from Multi-field Particle Volume Data Using Multi-dimensional Cluster Visualization

Lars Linsen; Tran Van Long; Paul Rosenthal; Stephan Rosswog IEEE Transactions on Visualization and Computer Graphics, 2008

Data sets resulting from physical simulations typically contain a multitude of physical variables. It is, therefore, desirable that visualization methods take into account the entire multi-field volume data rather than concentrating on one variable. We present a visualization approach based on surface extraction from multi-field particle volume data. The surfaces segment the data with respect to the underlying multi-variate function. ...


A novel approach of resolution enhancement with application in array processing of single snapshot

M. Zhang; W. Yang; L. Li IEEE Transactions on Antennas and Propagation, 1991

An approach based on spatial filter preprocessing is developed to enhance the resolution of current spectrum estimation algorithms and is applied to sensor array processing in the single snapshot case. The effective signal-to-noise ratio (SNR) and the accuracy of autocorrelation estimation are significantly improved through the use of this approach. Simulation results are presented to illustrate the improved performance achieved ...


Channel estimation for MC-CDMA with compensation of synchronization errors

Yuan Zhang; R. Hoshyar; R. Tafazolli IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004, 2004

In this paper, we investigate channel estimation for MC-CDMA in the presence of time and frequency synchronization errors. Channel estimation in MC-CDMA requires transmission of pilot tones, based on which MMSE interpolation or FFT-based interpolation algorithms are applied. Most channel estimation methods in the literature assume perfect synchronization. However, this condition is not guaranteed in the actual case, and channel ...


Frequency-wavenumber domain focusing under linear MIMO array configurations

Xiaodong Zhuge; Alexander Yarovoy 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012

This paper introduces a fast imaging algorithm oriented for linear MIMO array configurations. The image reconstruction process is performed in the frequency-wavenumber domain and requires a modified interpolation process among both transmit and receive apertures. The proposed algorithm corrects completely the range curvature in the near-field and is able to provide high quality images for short-range targets. The proposed algorithm ...


A fast piecewise-linear implementation of fuzzy controllers

A. Jimenez; F. Matia Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,, 1994

This paper discusses how it is possible to develop a fuzzy controller by means of a collection of points (guide points) and a linear interpolation between them, when some conditions are satisfied. The use of the product as t-norm and the bounded sum as s-norm, the use of normal and triangular membership functions and an adequate overlapping between them, are ...


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Educational Resources on Interpolation

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eLearning

Surface Extraction from Multi-field Particle Volume Data Using Multi-dimensional Cluster Visualization

Lars Linsen; Tran Van Long; Paul Rosenthal; Stephan Rosswog IEEE Transactions on Visualization and Computer Graphics, 2008

Data sets resulting from physical simulations typically contain a multitude of physical variables. It is, therefore, desirable that visualization methods take into account the entire multi-field volume data rather than concentrating on one variable. We present a visualization approach based on surface extraction from multi-field particle volume data. The surfaces segment the data with respect to the underlying multi-variate function. ...


A novel approach of resolution enhancement with application in array processing of single snapshot

M. Zhang; W. Yang; L. Li IEEE Transactions on Antennas and Propagation, 1991

An approach based on spatial filter preprocessing is developed to enhance the resolution of current spectrum estimation algorithms and is applied to sensor array processing in the single snapshot case. The effective signal-to-noise ratio (SNR) and the accuracy of autocorrelation estimation are significantly improved through the use of this approach. Simulation results are presented to illustrate the improved performance achieved ...


Channel estimation for MC-CDMA with compensation of synchronization errors

Yuan Zhang; R. Hoshyar; R. Tafazolli IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004, 2004

In this paper, we investigate channel estimation for MC-CDMA in the presence of time and frequency synchronization errors. Channel estimation in MC-CDMA requires transmission of pilot tones, based on which MMSE interpolation or FFT-based interpolation algorithms are applied. Most channel estimation methods in the literature assume perfect synchronization. However, this condition is not guaranteed in the actual case, and channel ...


Frequency-wavenumber domain focusing under linear MIMO array configurations

Xiaodong Zhuge; Alexander Yarovoy 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012

This paper introduces a fast imaging algorithm oriented for linear MIMO array configurations. The image reconstruction process is performed in the frequency-wavenumber domain and requires a modified interpolation process among both transmit and receive apertures. The proposed algorithm corrects completely the range curvature in the near-field and is able to provide high quality images for short-range targets. The proposed algorithm ...


A fast piecewise-linear implementation of fuzzy controllers

A. Jimenez; F. Matia Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,, 1994

This paper discusses how it is possible to develop a fuzzy controller by means of a collection of points (guide points) and a linear interpolation between them, when some conditions are satisfied. The use of the product as t-norm and the bounded sum as s-norm, the use of normal and triangular membership functions and an adequate overlapping between them, are ...


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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

  • 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."

  • Interpolation Techniques

    The projection of light rays onto the retina of the eye forms a two- dimensional image, but through combining the stereoscopic aspect of vision with other optical clues by means of some remarkably effective image- processing procedures, the viewer is able to perceive three-dimensional representations of scenes.From Images to Surfaces proposes and examines a specific image-processing procedure to account for this remarkable effect-a computational approach that provides a framework for understanding the transformation of a set of images into a representation of the shapes of surfaces visible in a scene. Although much of the analysis is applicable to any visual information processing system-biological or artificial-Grimson constrains his final choice of computational algorithms to those that are biologically feasible and consistent with what is known about the human visual system.In order to clarify the analysis, the approach distinguishes three independent levels: the computational theory itself, the algorithms employed, and the underlying implementation of the computation, in this case through the human neural mechanisms. This separation into levels facilitates the generation of specific models from general concepts.This research effort had its origin in a theory of human stereo vision recently developed by David Marr and Tomaso Poggio. Grimson presents a computer implementation of this theory that serves to test its adequacy and provide feedback for the identification of unsuspected problems embedded in it. The author then proceeds to apply and extend the theory in his analysis of surface interpolation through the computational methodology.This methodology allows the activity of the human early visual system to be followed through several stages: the Primal Sketch, in whi ch intensity changes at isolated points on a surface are noted; the Raw 2.5-D Sketch, in which surface values at these points are computed; and the Full 2.5-D Sketch, in which these values--ncluding stereo and motion perception--are interpolated over the entire surface. These stages lead to the final 3-D Model, in which the three-dimensional shapes of objects, in object- centered coordinates, are made explicit.

  • 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

  • Learning Motion Style Synthesis from Perceptual Observations

    This paper presents an algorithm for synthesis of human motion in specified styles. We use a theory of movement observation (Laban Movement Analysis) to describe movement styles as points in a multi-dimensional perceptual space. We cast the task of learning to synthesize desired movement styles as a regression problem: sequences generated via space-time interpolation of motion capture data are used to learn a nonlinear mapping between animation parameters and movement styles in perceptual space. We demonstrate that the learned model can apply a variety of motion styles to pre-recorded motion sequences and it can extrapolate styles not originally included in the training data.

  • Name Index

    The projection of light rays onto the retina of the eye forms a two- dimensional image, but through combining the stereoscopic aspect of vision with other optical clues by means of some remarkably effective image- processing procedures, the viewer is able to perceive three-dimensional representations of scenes.From Images to Surfaces proposes and examines a specific image-processing procedure to account for this remarkable effect-a computational approach that provides a framework for understanding the transformation of a set of images into a representation of the shapes of surfaces visible in a scene. Although much of the analysis is applicable to any visual information processing system-biological or artificial-Grimson constrains his final choice of computational algorithms to those that are biologically feasible and consistent with what is known about the human visual system.In order to clarify the analysis, the approach distinguishes three independent levels: the computational theory itself, the algorithms employed, and the underlying implementation of the computation, in this case through the human neural mechanisms. This separation into levels facilitates the generation of specific models from general concepts.This research effort had its origin in a theory of human stereo vision recently developed by David Marr and Tomaso Poggio. Grimson presents a computer implementation of this theory that serves to test its adequacy and provide feedback for the identification of unsuspected problems embedded in it. The author then proceeds to apply and extend the theory in his analysis of surface interpolation through the computational methodology.This methodology allows the activity of the human early visual system to be followed through several stages: the Primal Sketch, in whi ch intensity changes at isolated points on a surface are noted; the Raw 2.5-D Sketch, in which surface values at these points are computed; and the Full 2.5-D Sketch, in which these values--ncluding stereo and motion perception--are interpolated over the entire surface. These stages lead to the final 3-D Model, in which the three-dimensional shapes of objects, in object- centered coordinates, are made explicit.

  • 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

  • Support Vector Machines on a Budget

    The standard Support Vector Machine formulation does not provide its user with the ability to explicitly control the number of support vectors used to define the generated classifier. We present a modified version of SVM that allows the user to set a budget parameter B and focuses on minimizing the loss attained by the B worst-classified examples while ignoring the remaining examples. This idea can be used to derive sparse versions of both L1-SVM and L2-SVM. Technically, we obtain these new SVM variants by replacing the 1-norm in the standard SVM formulation with various interpolation-norms. We also adapt the SMO optimization algorithm to our setting and report on some preliminary experimental results.



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