Autocorrelation

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Autocorrelation is the cross-correlation of a signal with itself. (Wikipedia.org)






Conferences related to Autocorrelation

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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.


2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC 2012)

PIMRC conference enjoys today wide respect and represents a new trend in international conferences, one which is well suited to the evolving global market. It is uniquely identified by the following features: balance among academia, industry, and governmental organizations; international technical program; flexible organization.


2012 IEEE International Frequency Control Symposium (FCS)

The 2012 IEEE International Frequency Control Symposium is one of the leading international technical conferences for research, development, and applications of frequency control. Topics include, Materials, Filters, Resonators, MEMS, Oscillators, Synthesizers, Noise, Timekeeping, Optical and Microwave Atomic Standards, Sensors and Transducers.


2012 IEEE Symposium on Electrical & Electronics Engineering (EEESYM)

Automation, Mechatronics & Robotics - Business, Management & Finance in Industries - Computer Applications - Electronics & Circuits - Engineering Education - Engineering Management - Lasers & Optics - Network & Communications Technology - Power & Energy - RF and Microwave - Signal & Image Processing - Women in Engineering.


2012 IEEE Vehicular Technology Conference (VTC Fall)

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.


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Periodicals related to Autocorrelation

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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.


Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


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Xplore Articles related to Autocorrelation

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Spatial scales of tropical precipitation inferred from TRMM microwave imager data

D. F. Smith; A. J. Gasiewski; D. L. Jackson; G. A. Wick IEEE Transactions on Geoscience and Remote Sensing, 2005

The local spatial scales of tropical precipitating systems were studied using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rate imagery from the TRMM satellite. Rain rates were determined from TMI data using the Goddard Profiling (GPROF) Version 5 algorithm. Following the analysis of Ricciardulli and Sardeshmukh (RS), who studied local spatial scales of tropical deep convection using global ...


SASI: a new texture descriptor for content based image retrieval

A. Carkacioglu; F. Yarman-Yural Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001

A new texture descriptor, namely, statistical analysis of structural information (SASI) is introduced as a representation of texture. SASI is based on the statistics of clique autocorrelation functions calculated over a set of directional moving windows. SASI defines a set of windows to extract and measure various structural properties of texture by using a spatial multiresolution method. Although it works ...


Optimal supports for linear predictive models

R. Rajagopalan; M. T. Orchard; K. Ramchandran IEEE Transactions on Signal Processing, 1996

The problem of finding the optimal set of causal pixels (support) for use in linear predictive models is addressed. After presenting counterexamples to popular intuitions about supports, a general result relating the distortion incurred with a small support to optimal coefficients of a larger support is derived. A geometrical interpretation is provided. Two algorithms that optimally increase/decrease support sizes by ...


Multiphase Complementary Codes

R. Sivaswamy IEEE Transactions on Information Theory, 1978

A new class of complementary codes, similar to the complementary series of Golay but having multiphase elements, have been found to exist with specific complementary aperiodic complex autocorrelation functions. These new codes, called multiphase complementary codes, form a class of generalized complementary codes, of which the Golay complementary series can be considered to be a particular biphase subclass. Unlike Golay ...


Fault tolerant FIR adaptive filters with improved convergence behavior

1993 IEEE International Symposium on Circuits and Systems, 1993

First Page of the Article ![](/xploreAssets/images/absImages/00692784.png)


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Educational Resources on Autocorrelation

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eLearning

Spatial scales of tropical precipitation inferred from TRMM microwave imager data

D. F. Smith; A. J. Gasiewski; D. L. Jackson; G. A. Wick IEEE Transactions on Geoscience and Remote Sensing, 2005

The local spatial scales of tropical precipitating systems were studied using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rate imagery from the TRMM satellite. Rain rates were determined from TMI data using the Goddard Profiling (GPROF) Version 5 algorithm. Following the analysis of Ricciardulli and Sardeshmukh (RS), who studied local spatial scales of tropical deep convection using global ...


SASI: a new texture descriptor for content based image retrieval

A. Carkacioglu; F. Yarman-Yural Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001

A new texture descriptor, namely, statistical analysis of structural information (SASI) is introduced as a representation of texture. SASI is based on the statistics of clique autocorrelation functions calculated over a set of directional moving windows. SASI defines a set of windows to extract and measure various structural properties of texture by using a spatial multiresolution method. Although it works ...


Optimal supports for linear predictive models

R. Rajagopalan; M. T. Orchard; K. Ramchandran IEEE Transactions on Signal Processing, 1996

The problem of finding the optimal set of causal pixels (support) for use in linear predictive models is addressed. After presenting counterexamples to popular intuitions about supports, a general result relating the distortion incurred with a small support to optimal coefficients of a larger support is derived. A geometrical interpretation is provided. Two algorithms that optimally increase/decrease support sizes by ...


Multiphase Complementary Codes

R. Sivaswamy IEEE Transactions on Information Theory, 1978

A new class of complementary codes, similar to the complementary series of Golay but having multiphase elements, have been found to exist with specific complementary aperiodic complex autocorrelation functions. These new codes, called multiphase complementary codes, form a class of generalized complementary codes, of which the Golay complementary series can be considered to be a particular biphase subclass. Unlike Golay ...


Fault tolerant FIR adaptive filters with improved convergence behavior

1993 IEEE International Symposium on Circuits and Systems, 1993

First Page of the Article ![](/xploreAssets/images/absImages/00692784.png)


More eLearning Resources

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IEEE-USA E-Books

  • Statistical Measures of Dependence for Financial Data

    This chapter provides the statistical measures of dependence for financial data. The analysis of financial and econometric data is typified by non- Gaussian multivariate observations that exhibit complex dependencies: heavy- tailed and skewed marginal distributions are commonly encountered; serial dependence, such as autocorrelation and conditional heteroscedasticity. When data are assumed to be jointly Gaussian, all dependence is linear, and therefore only pairwise among the variables. In this setting, Pearson's product-moment correlation coefficient uniquely characterizes the sign and strength of any such dependence. The chapter shows that copulas can be used to model the dependence between random variables. It turns our attention to the dependence structure itself, and when appropriate makes connections to copulas. The chapter describes different types of dependence, and then provides theoretical background.

  • A Simplified Derivation of Linear Least Square Smoothing and Prediction TheoryDecimal classification: 510. Original manuscript received by the Institute. July 13,1949; revised manuscript received. January 17, 1950.

    The central results of the Wiener-Koimogoroff smoothing and prediction theory for stationary time series are developed by a new method. The approach is motivated by physical considerations based on electric circuit theory and does not involve integral equations or the autocorrelation function. The cases treated are the ¿inftnite lag¿ smoothinl problem, the case of pure prediction (without noise), and the general smoothing prediction problem. Finally, the basic assumptions of the theory are discussed in order to clarify the question of when the theory will be appropriate, and to avoid possible misapplication.

  • Spread Spectrum Systems

    In spread spectrum systems the transmit signal occupies a wider spectrum than required by the symbol rate. Slow and fast Frequency Hopping (FH) changes the carrier frequencies, and can be used for multiple access in synchronized and unsynchronized systems. In Code Division Multiple Access (CDMA), the data sequences are multiplied by spreading sequences with short chip duration, thus increasing the occupied bandwidth by the ï¿¿ï¿¿ï¿¿spreading factorï¿¿ï¿¿ï¿¿. Spreading sequences with suitable crosscorrelation (and autocorrelation) properties allow separation of users: pseudonoise (PN) sequences like maximum- length (m-) sequences, Gold-, and Kasami-sequences; Walsh-Hadamard codes and Orthogonal Variable Spreading Factor (OVSF) codes. In delay-dispersive channels, Rake receivers consisting of multiple correlators (fingers) collect the energy contained in different multipath components. Synchronization of the receivers to the available signals occurs in two steps: acquisition and tracking. CDMA allows universal frequency reuse (i.e., reuse distance one). Inter-user interference (consisting of intra-cell and inter-cell interference) is noise-like. Randomization of inter-cell interference is effected by multiplying the signals in different cells with different scrambling codes. Power control ensures that no single user provides dominant intra-cell interference (in the uplink). Near the cell edge, soft handover ensures good transmission quality through macrodiversity. Multiuser detection (MUD) is based on exploiting the structure of interference to mitigate its effect on the desired signal. Linear MUDs include decorrelating receivers and MMSE receivers. Nonlinear MUDs include the (optimum) multiuser MLSE as well as successive interference cancellation (SIC) and parallel interference cancellation (PIC). Time hopping impulse radio, mostly used in ultrawideband (UWB) communicat ions, represents each symbol by a sequence of pulses. Transmitted-reference signals allow simple receivers.

  • No title

    This book describes several modules of the Code Excited Linear Prediction (CELP) algorithm. The authors use the Federal Standard-1016 CELP MATLAB® software to describe in detail several functions and parameter computations associated with analysis-by-synthesis linear prediction. The book begins with a description of the basics of linear prediction followed by an overview of the FS-1016 CELP algorithm. Subsequent chapters describe the various modules of the CELP algorithm in detail. In each chapter, an overall functional description of CELP modules is provided along with detailed illustrations of their MATLAB® implementation. Several code examples and plots are provided to highlight some of the key CELP concepts. Link to MATLAB® code found within the book Table of Contents: Introduction to Linear Predictive Coding / Autocorrelation Analysis and Linear Prediction / Line Spectral Frequency Computation / Spectral Distortion / The Codebook Search / The FS-1016 Decoder

  • Random Signals

    This chapter provides an overview of integration of the Gaussian probability density function and the Q-function. It explains the weighted sum of random variables and properties of Gaussian variables. The chapter presents the central limit theorem and ensembles average, autocorrelation functions of random processes. It also explores statistical properties of additive white Gaussian noise (AWGN). The chapter provides step-by-step code exercises and instructions to implement execution sequences. The MATLAB command randn(1,b) generates a 1??b vector whose elements are realizations of independent and identically distributed Gaussian random variables with zero mean and unit variance. The chapter summarizes the analytical relationship among the input, the output, and the impulse response of a linear system in the time domain. It is designed to help teach and understand communication systems using a classroom-tested, active learning approach.

  • FrequencyModulated Pulse

    Two additional frequency modulated signals are described that are different from the linear-FM signal discussed in the previous chapter. The first is the Costas signal, in which the frequency evolution is random-like, in contrast with the linear evolution in LFM. The resulting ambiguity function (AF) has a thumbtack shape, in contrast to the ridge found in LFM. The Costas signal is explained in detail, and the Welch construction algorithms are described. Appendix 5.1 includes a MATLAB code that implements those algorithms. Because LFM exhibited relatively high autocorrelation sidelobes, some form of amplitude weighting was necessary in order to reshape the spectrum and thus reduce the autocorrelation sidelobes. In nonlinear-FM, the second signal discussed in this chapter, the spectrum is shaped not by amplitude weighting, but by spending more time in the frequencies that need to be emphasized. Several different nonlinear frequency evolution laws and their performances are described.

  • Optimal Linear Estimators for Quantized Stationary Processes

    This chapter contains sections titled: Introduction, Autocorrelation of the Quantizer Output, A New Interpretation of the Describing function, Optimal Linear Filters for Quantized Measurements, Joint Optimization of the Quantizer and Filter, Summary

  • Bit-Plane Analysis

    This chapter contains sections titled: Visual Steganalysis Autocorrelation Features Binary Similarity Measures Evaluation and Comparison

  • Fractal Analysis of Heart Rate Variability

    This chapter contains sections titled: Introduction The fBm Model The Autocorrelation Function for DFGN The Probability Density Function for DFGN A Maximum Likelihood Estimator for DFGN PSD Estimators for fBm and DFGN A Wavelet Estimator for DFGN The Heart Rate Variability Signal This chapter contains sections titled: References

  • Coherent Train of Diverse Pulses

    The chapter describes methods for pulse to pulse diversity. The methods described are used for reduction in the height of the recurrent (range) lobes of the autocorrelation function (ACF), reduction of the near range sidelobes (namely around the mainlobe) and for increasing the overall bandwidth of the signal, while maintaining relatively narrow instantaneous bandwidth. The signals described include: Phase coded pulse train - used to lower range recurrent lobes. Stepped-frequency signal  -  used for increasing bandwidth. The chapter also describes a simple processor that is often used with it - the stretch- processor. The specific case of a stepped frequency LFM pulse train is described in details together with means of nullifying ACF grating lobes and Costas ordering the pulses. Complementary phase coded pulse trains yield zero ACF sidelobes around the mainlobe area. Methods for generating binary and polyphase complementary codes for different lengths and set size are described. Signals based on complementary sets based on the PONS construction and orthogonal matrices are described with more details. Sub-complementary phase coded pulse trains. Orthogonal coded pulse trains, with focus on orthogonal coded LFM pulse trains, LFM-LFM pulse trains and LFM-NLFM pulse trains.



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