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

Conferences related to Autocorrelation

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2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

The Conference focuses on all aspects of instrumentation and measurement science andtechnology research development and applications. The list of program topics includes but isnot limited to: Measurement Science & Education, Measurement Systems, Measurement DataAcquisition, Measurements of Physical Quantities, and Measurement Applications.

2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore

2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)

Science, technology and applications spanning the millimeter-waves, terahertz and infrared spectral regions

2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

For its 20th year edition, the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019, returns to the country that saw its birth, France. Held in Cannes, in the heart of the world renown “French Riviera” (Cote d’Azur in French), the SPAWC 2019 will exhibit a technical program complete with high profile plenaries, invited and contributed papers, all appearing under IEEE explore. A flagship workshop of the IEEE SP Society SPCOM technical committee, SPAWC 2019 will combine cutting edge research in the fields of signal processing, statistical learning, communication theory, wireless networking and more, together with an exciting social program on the glamorous and sunny Riviera.

2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

International Geosicence and Remote Sensing Symposium (IGARSS) is the annual conference sponsored by the IEEE Geoscience and Remote Sensing Society (IEEE GRSS), which is also the flagship event of the society. The topics of IGARSS cover a wide variety of the research on the theory, techniques, and applications of remote sensing in geoscience, which includes: the fundamentals of the interactions electromagnetic waves with environment and target to be observed; the techniques and implementation of remote sensing for imaging and sounding; the analysis, processing and information technology of remote sensing data; the applications of remote sensing in different aspects of earth science; the missions and projects of earth observation satellites and airborne and ground based campaigns. The theme of IGARSS 2019 is “Enviroment and Disasters”, and some emphases will be given on related special topics.

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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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Most published Xplore authors for Autocorrelation

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Xplore Articles related to Autocorrelation

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Photorefractive materials and devices

[{u'author_order': 1, u'affiliation': u'University of Southern California', u'authorUrl': u'', u'full_name': u'J. Feinberg', u'id': 37330902700}] Digest on Nonlinear Optics: Materials, Phenomena and Devices, 1990


Essay - Wacky electoral skepticism

[{u'author_order': 1, u'affiliation': u'North Dakota State University', u'authorUrl': u'', u'full_name': u'R. Green', u'id': 38182572600}] IEEE Potentials, 2004


Author's reply

[{u'author_order': 1, u'affiliation': u'Hanyang University', u'full_name': u'Youngyearl Han'}] IEEE Transactions on Vehicular Technology, 2000


Corrections to "Effects of bursty crosstalk in DSL"

[{u'author_order': 1, u'affiliation': u'Ikanos Communications', u'authorUrl': u'', u'full_name': u'F. Ramirez-Mireles', u'id': 38273292900}] IEEE Communications Letters, 2002

In the above-named article, corrections are made to the last sentence of the Introduction's second paragraph and the second equation of the Appendix.

Session: linear complexity

[] 1988 IEEE International Symposium on Information Theory., 1988

The following topics are dealt with: self-decimated sequences; arbitrary finite field sequences; and jump complexity.<<ETX>>

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  • Appendix IV: Stationarity, Ergodicity, and Autocorrelation Functions of Random Processes

  • Synchronization

    OFDM systems are very sensitive and vulnerable to synchronization errors. In this chapter, the authors look into synchronization errors and their effects, review synchronization techniques, and design ML synchronization block in the OFDM system. Synchronization techniques can be classified into data‐aided methods, decision‐directed methods, and non‐data‐aided methods. Many synchronization techniques are based on two important algorithms: autocorrelation and crosscorrelation. In OFDM systems, coarse timing synchronization and fine timing synchronization are usually based on autocorrelation and crosscorrelation, respectively. The purpose of the OFDM synchronization block is to detect an OFDM symbol, find the time and frequency offset, and maintain the orthogonality of each subcarrier. The chapter briefly investigates the hardware design issues of the OFDM synchronization. An OFDM synchronization block requires a real time implementation and a large size memory. The ASIC design would be the best solution.

  • Adaptive High-Resolution Sensor Waveform Design for Tracking

    Recent innovations in modern radar for designing transmitted waveforms, coupled with new algorithms for adaptively selecting the waveform parameters at each time step, have resulted in improvements in tracking performance. Of particular interest are waveforms that can be mathematically designed to have reduced ambiguity function sidelobes, as their use can lead to an increase in the target state estimation accuracy. Moreover, adaptively positioning the sidelobes can reveal weak target returns by reducing interference from stronger targets. The manuscript provides an overview of recent advances in the design of multicarrier phase-coded waveforms based on Bjorck constant- amplitude zero-autocorrelation (CAZAC) sequences for use in an adaptive waveform selection scheme for mutliple target tracking. The adaptive waveform design is formulated using sequential Monte Carlo techniques that need to be matched to the high resolution measurements. The work will be of interest to both practitioners and researchers in radar as well as to researchers in other applications where high resolution measurements can have significant benefits. Table of Contents: Introduction / Radar Waveform Design / Target Tracking with a Particle Filter / Single Target tracking with LFM and CAZAC Sequences / Multiple Target Tracking / Conclusions

  • MATLAB® Software for the Code Excited Linear Prediction Algorithm: The Federal Standard-1020

    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

  • 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

  • Sensitivities of Mean Square Estimation Error with Respect to Quantizer Parameters

    This chapter contains sections titled: Change in MSEE due to Changes in Output Autocorrelation, Partial Derivatives of b(m) with Respect to {dn}, Partial Derivatives of b(m) with respect to {yn}

  • Quantum Signal Processing

    In signal processing, the Wigner distribution is used as a quadratic time‐frequency representation derived from the notion of autocorrelation. Wigner distribution was introduced in the context of quantum physics, to introduce quantum corrections to statistical physics. It shows a remarkable property, which is that it can be defined in an equivalent manner to the frequency version of the signal, obtained by the Fourier transform (TF). Gauss sums are similar to Fourier sums with the clear difference that the index of summation appears in the quadratic phase in a location in a linear manner. This distribution can be interpreted as the signal's power spectral density. This chapter discusses the factorization properties of different Gauss sums. Heisenberg's view is the following: physical quantities in quantum mechanics can only be processed with a non‐commutative algebra. This leads to envisage that quantum mechanics can only be understood, from a geometrical point of view, via a non‐commutative geometry.

  • Multiple‐Access Channels

    This chapter focuses on uplink multiple‐access (MA) channels, which can be classified into two cases of flat fading and frequency‐selective fading. It investigates the mutual information of various MA schemes in two cases: AWGN and flat‐fading channels. For illustrating the practical application of MA schemes, the chapter considers IS‐95A CDMA and long term evolution (LTE) systems. In CDMA, a direct consequence of spanning each symbol of a user over its signature sequence is the spreading of its power spectrum. Processing gain associated with spreading spectrum in a CDMA system has an intuitive explanation. The chapter presents commonly used pseudo‐random (PN) sequences include m‐sequences, Walsh sequences, Gold sequences, and constant amplitude zero autocorrelation (CAZAC) sequences. CAZAC sequences have been adopted by third generation partnership project (3GPP) LTE as preamble signatures for the random access channel (RACH) in the uplink.


    This chapter provides the foundation for modeling and finding practical design solutions to communication system performance specifications. It describes the commonly used waveform modulations characterized as amplitude modulation (AM), phase modulation (PM), and frequency modulation (FM) waveforms. The chapter discusses the discrete Fourier transform (DFT), the fast Fourier transform (FFT), the pipeline implementation of the FFT, and applications involving waveform detection, interpolation, and power spectrum estimation. It introduces the concept of random variables and various probability density functions (pdf) and cumulative distribution functions (cdf) for continuous and discrete random variables. It focuses on characterization of several window functions that are used to improve the performance the FFT, decimation filtering, and signal parameter estimation. The chapter focuses on the subject of autocorrelation and crosscorrelation of real and complex deterministic functions and concludes with a list of frequently used mathematical formulas.

  • Measurement Uncertainty in the Reverberation Chamber

    Due to the complicated and time‐varying test conditions, reverberation chamber (RC) measurement data are usually analysed from a statistical point of view. This chapter investigates the measurement uncertainty in the RC. The measurement uncertainty can be assessed by repeating the reference measurement several times with different positions and orientations of the reference antenna inside the RC. According to the statistics, the RC measurement uncertainty depends on its independent sample numbers. The chapter describes the autocorrelation function (ACF) method and spatial degrees of freedom (DoF) method for estimating the number of independent samples. The uncertainty models using the ACF method or DoF method relies on accurate estimation of the number of independent samples. For the sake of completeness and to facilitate the uncertainty analysis, the chapter briefly repeats the standard method for antenna efficiency measurement with slightly different notations.

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