Autocorrelation
15,922 resources related to Autocorrelation
IEEE Organizations related to Autocorrelation
Back to TopConferences related to Autocorrelation
Back to Top2012 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, knowledgebased systems, and high performance computing.
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 worldclass plenary speakers, panel sessions, tutorials, and both technical and applicationbased sessions.
More Conferences
Periodicals related to Autocorrelation
Back to TopAntennas 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.
More Periodicals
Xplore Articles related to Autocorrelation
Back to TopSpatial 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. YarmanYural 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 Xplore Articles
Educational Resources on Autocorrelation
Back to TopeLearning
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. YarmanYural 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
IEEEUSA EBooks

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 productmoment 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.

The central results of the WienerKoimogoroff 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 Â¿inftnite lagÂ¿ 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.

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 Kasamisequences; WalshHadamard codes and Orthogonal Variable Spreading Factor (OVSF) codes. In delaydispersive 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). Interuser interference (consisting of intracell and intercell interference) is noiselike. Randomization of intercell interference is effected by multiplying the signals in different cells with different scrambling codes. Power control ensures that no single user provides dominant intracell 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. Transmittedreference signals allow simple receivers.

This book describes several modules of the Code Excited Linear Prediction (CELP) algorithm. The authors use the Federal Standard1016 CELP MATLAB® software to describe in detail several functions and parameter computations associated with analysisbysynthesis linear prediction. The book begins with a description of the basics of linear prediction followed by an overview of the FS1016 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 FS1016 Decoder

This chapter provides an overview of integration of the Gaussian probability density function and the Qfunction. 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 stepbystep 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 classroomtested, active learning approach.

Two additional frequency modulated signals are described that are different from the linearFM signal discussed in the previous chapter. The first is the Costas signal, in which the frequency evolution is randomlike, 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 nonlinearFM, 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

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. Steppedfrequency signal Â Â 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. Subcomplementary phase coded pulse trains. Orthogonal coded pulse trains, with focus on orthogonal coded LFM pulse trains, LFMLFM pulse trains and LFMNLFM pulse trains.