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Statistics is the study of the collection, organization, and interpretation of data. (Wikipedia.org)






Conferences related to Statistics

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2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.


2019 IEEE 28th International Symposium on Industrial Electronics (ISIE)

The conference will provide a forum for discussions and presentations of advancements inknowledge, new methods and technologies relevant to industrial electronics, along with their applications and future developments.


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.


2019 IEEE International Professional Communication Conference (ProComm)

The scope of the conference includes the study, development, improvement, and promotion ofeffective techniques for preparing, organizing, processing, editing, collecting, conserving,teaching, and disseminating any form of technical information by and to individuals and groupsby any method of communication. It also includes technical, scientific, industrial, and otheractivities that contribute to the techniques and products used in this field.


2019 IEEE International Symposium on Electromagnetic Compatibility - EMC 2019

The IEEE Electromagnetic Compatibility Society is the world's largest organization dedicated to the development and distribution of information, tools and techniques for reducing electromagnetic interference. The society's field of interest includes standards, measurement techniques and test procedures, instrumentation, equipment and systems characteristics, interference control techniques and components, education, computational analysis, and spectrum management, along with scientific, technical, industrial, professional or other activities that contribute to this field


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Periodicals related to Statistics

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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.


Antennas and Wireless Propagation Letters, IEEE

IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.


Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


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.


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Most published Xplore authors for Statistics

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Xplore Articles related to Statistics

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Design of low rank estimators for higher-order statistics based on the second-order statistics

Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics. SPW-HOS '99, 1999

Higher-order statistics (HOS) are well known for their robustness to additive Gaussian noise and their ability to preserve phase. HOS estimates on the other hand, have been criticised for high complexity and the need of long data in order to maintain low variance. Rank reduction offers a general principle for reduction of estimator variance and complexity. In this paper we ...


An emerging alliance: higher order statistics should partner conventional statistics in digital signal processing applications

IEE Colloquium on Higher Order Statistics in Signal Processing: Are They of Any Use?, 1995

The conjecture of the paper is that higher order statistics are best used in combination with conventional second order statistics; not in isolation. This is demonstrated by showing some established and new examples where this proposal has been utilised. A conventional, second order, spectral estimator stabilises the statistical performance of higher order spectral estimation techniques. The performance of an adaptation ...


Big data for government policy: Potential implementations of bigdata for official statistics in Indonesia

2017 International Workshop on Big Data and Information Security (IWBIS), 2017

Big Data is an umbrella term for explosion in the quantity and diversity of high frequency digital data and it is not usually coming from traditional sources. The speed and frequency by which data is produced and collected - by an increasing number of sources - is responsible for today's data deluge: the amount of available digital data is projected ...


Isolated word recognition using high-order statistics and time-delay neural networks

Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, 1997

In this paper, two isolated word recognition methods based on high-order statistics and a time-delay neural network (TDNN) for recognition of Farsi spoken digits have been studied. The adopted speech recognition system consists of four modules, namely, a preprocessor, endpoints' detector, feature extractor and classifier. The first method estimates the AR parameters of speech based on the third- and fourth-order ...


Variability in higher order statistics of measured shallow-water shipping noise

Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, 1997

Many underwater acoustic signal processing algorithms are designed for use in stationary and/or Gaussian noise. While these assumptions are often valid for applications in deep water ocean areas, they may not be appropriate for shallow water areas, especially in the presence of local shipping activity. Local shipping also produces spatial correlation in the noise and introduces additional complexity for multichannel ...


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Educational Resources on Statistics

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IEEE.tv Videos

Dictionary Learning: Principles, Algorithms, Guarantees
Louis Scharf receives the IEEE Jack S. Kilby Signal Processing Medal - Honors Ceremony 2016
Broadening Participation in Computing and Empowering Female Leaders with Maria Klawe - IEEE WIE ILC 2017
Cathy Chen from Exponent at WIE ILC 2016
Technical Program Overview - Antonio Skarmeta - 5G World Forum Santa Clara 2018
Internet of Things Panelist - Clint Andrews: 2016 Technology Time Machine
Plotting the Course for Nationwide 5G Deployment - Egil Gronstad - 5G World Forum Santa Clara 2018
Building the Bridge to the Future - Mary Ellen Randall - Opening Ceremony: Sections Congress 2017
Netflix's Chris Pouliot: How to Build a Data Science Team from Scratch
IEEEXtreme: IEEE’s Largest Programming Competition - Prasanth Mohan - Ignite: Sections Congress 2017
IEEE Women In Engineering - Bozenna Pasik-Duncan - Ignite: Sections Congress 2017
IEEE's Leah Jamieson focuses on Women Accelerating Change through Philanthropy - 2016 Women in Engineering Conference
IMS 2014: Wideband mmWave Channels: Implications for Design and Implementation of Adaptive Beam Antennas
2015 IEEE Honors: IEEE Richard W. Hamming Medal - Imre Csiszar
IEEE Internet Initiative - Mission and Goals; Review of Previous ETAP Forums; Goals for ETAP Namibia: Maike Luiken - ETAP Forum Namibia, Africa 2017
A Bayesian Approach for Spatial Clustering - IEEE CIS Webinar
Jim Prendergast - Opening Ceremony: Sections Congress 2017
Tim Winters: Internet of Things IP Testing Service - IPv6 IoT InterOp-Ware Industry Forum Panel: WF IoT 2016
Vladimir Cherkassky - Predictive Learning, Knowledge Discovery and Philosophy of Science

IEEE-USA E-Books

  • Design of low rank estimators for higher-order statistics based on the second-order statistics

    Higher-order statistics (HOS) are well known for their robustness to additive Gaussian noise and their ability to preserve phase. HOS estimates on the other hand, have been criticised for high complexity and the need of long data in order to maintain low variance. Rank reduction offers a general principle for reduction of estimator variance and complexity. In this paper we consider the problem of designing low-rank estimators for third-order statistics (TOS). We propose a method for choosing the rank reduced transformation matrix based on the second-order statistics of the signal. Results indicate that the proposed approach significantly reduces the mean square error associated with the TOS estimates. Simulation results are presented to also demonstrate the advantages of using low rank TOS estimates for blind system estimation.

  • An emerging alliance: higher order statistics should partner conventional statistics in digital signal processing applications

    The conjecture of the paper is that higher order statistics are best used in combination with conventional second order statistics; not in isolation. This is demonstrated by showing some established and new examples where this proposal has been utilised. A conventional, second order, spectral estimator stabilises the statistical performance of higher order spectral estimation techniques. The performance of an adaptation algorithm based upon a higher order error norm is regularised by the inclusion of a second order moment. The statistical properties of AR parameter estimates are improved through a combination of second and third order statistics. Finally, a two-stage adaptive equalisation algorithm uses conventional statistics to remove amplitude distortion and higher order statistics to overcome a non-minimum phase channel each working with preferred signals. Simulation studies are included to support the assertion.<<ETX>>

  • Big data for government policy: Potential implementations of bigdata for official statistics in Indonesia

    Big Data is an umbrella term for explosion in the quantity and diversity of high frequency digital data and it is not usually coming from traditional sources. The speed and frequency by which data is produced and collected - by an increasing number of sources - is responsible for today's data deluge: the amount of available digital data is projected to increase by an annual 40%. “Big Data for Development” is a concept that refers to the identification of sources of Big Data relevant to policy and planning of development programmes. It differs from both “traditional” development data and what the private sector and mainstream media call Big Data. Potential applicability of “Big Data for Development” at the most general level, when it is properly analysed, these new data can provide snapshots of the well-being of populations at high frequency, high degrees of granularity, and from a wide range of angles, narrowing both time and knowledge gaps. This research discussed several possible implementations of Big Data to the official statistics in Indonesia. Furthermore, three case studies would be discussed: (1) predicting inter-city commuting patterns using twitter, (2) developing a statistical model to nowcast food prices using crowdsourcing, and (3) Mobile Position Data for Tourism Statistics. The results show similar trend between crowdsourcing approach and BPS Survey for all commodities, between the twitter approach and the commuter survey 2014. For the MPD approach for tourist statistics, the number of visits based on the roaming and the visits based on the immigration are similar. The study reveals potential implementations of Bigdata in complementing official statistics for government policy in Indonesia.

  • Isolated word recognition using high-order statistics and time-delay neural networks

    In this paper, two isolated word recognition methods based on high-order statistics and a time-delay neural network (TDNN) for recognition of Farsi spoken digits have been studied. The adopted speech recognition system consists of four modules, namely, a preprocessor, endpoints' detector, feature extractor and classifier. The first method estimates the AR parameters of speech based on the third- and fourth-order cumulants using high-order Yule- Walker, W-slice and 1-D slice approaches. In the second, method, statistical features are extracted from the estimated high-order probability density function (pdf) of thresholded amplitude features. For each pdf estimate, the values of mean, variance, third order moment and entropy are computed. The total number of features for each frame of approximate length of 15 ms is 16. The adopted TDNN has 16 nodes in its input layer, 10 nodes in its output layer and two hidden layers. The learning rule of the adopted TDNN that is based on the backpropagation rule has been modified to decrease the training time. Computer simulation results obtained from recognizing 10 Farsi digits spoken by different speakers shows that the first method has a better recognition rate while the second method necessitates less computation.

  • Variability in higher order statistics of measured shallow-water shipping noise

    Many underwater acoustic signal processing algorithms are designed for use in stationary and/or Gaussian noise. While these assumptions are often valid for applications in deep water ocean areas, they may not be appropriate for shallow water areas, especially in the presence of local shipping activity. Local shipping also produces spatial correlation in the noise and introduces additional complexity for multichannel processing. In this paper, two 30-minute sets of ambient ocean noise, recorded near the San Diego, California coast, are analyzed for stationarity and Gaussianity using the Kolmogorov- Smirnov test. Since processing algorithms based on higher order statistics often assume Gaussianity, time-dependent fluctuations in the third and fourth order cumulants are also analyzed. The analysis reveals significant variability in the time lengths of stationary periods, and episodic periods of nonGaussianity that last for up to five minutes. Statistical fluctuations appear predominantly in the second and fourth order cumulants rather than the third order cumulant. The shipping noise is also shown to be correlated between pairs of hydrophones with the level of correlation varying over time and the correlation ranging from positive to negative with increasing channel separation.

  • Multipath time delay estimation using higher order statistics

    This paper addresses the problem of time delay estimation (TDE) in spatially correlated noises. Two cases are considered: (i) TDE of non-Gaussian signal in spatially correlated Gaussian noises; and (ii) TDE of Gaussian signal in spatially correlated non-Gaussian noises. For the first case, a new approach based upon the use of higher order statistics of the measurements is proposed; for the second case, a hybrid approach by using higher and second order statistics of the measurements is suggested. Simulation examples are presented to illustrate the effectiveness of these approaches.

  • The interdiscipline of electronic commerce statistics and international trade statistics

    This document studies the problem of E-commerce as viewed from international trade statistics. It analyses the similarities and differences of the trade volume statistics of E-commerce and international trade statistics. It tries to offer suggestions for putting E-commerce statistics in international trade in practice according to the recent Manual on Statistics of International Trade.

  • Sampling jitter detection using higher-order statistics

    The spectrum of a signal subjected, to sampling jitter can be significantly different from the spectrum of the same signal sampled without jitter. The first part of the paper shows that the spectrum of a continuous Gaussian signal can be reconstructed from a combined use of the sampled (with jitter) signal second and fourth-order statistics. This spectral reconstruction is then used to detect the presence or absence of jitter in a sampled signal. A likelihood ratio detector based on the spectral corrective term is studied. It gives a reference to which suboptimal detectors can be compared.

  • Inter symbol interference cancellation for a mobile cellular receiver using lower and higher order statistics

    A code division multiple access (CDMA) signal which is subjected to multipath and other causes of intersymbol interference (ISI) must function in a low SNR environment by virtue of being a spread spectrum signal. In such an environment conventional ISI cancellation techniques, such as least mean square (LMS) equalisation, will not operate satisfactorily. Therefore an equalisation scheme which is insensitive to extremely high levels of Gaussian noise must be developed. In this paper such a scheme which employs both second-order and higher order statistics and exploits the characteristics of CDMA channels has been developed. The algorithm is effective against both mean square error (MSE) and ISI as it employs a cost function which includes both second-order and 4th-order cumulant terms.

  • Comparative Study of Sports Statistics Textbooks and Other Disciplines' Statistics Textbooks

    Through the literature review, mathematical statistics and comparative studies have been done for the proportion of some sections in seven kinds of statistics textbooks. The seven kinds of statistics textbooks is respectively about sports, education, psychology, business, socio-economics, biology and medicine. The results show that sports statistics textbook should enforce the composition of research design, data collection and collation, and statistical reports, it is also suggested to pay more attention to the applicability of textbooks, the initiative of students and the introduction of statistical software. So this project aims at providing theoretical supports for statistics textbooks to be more conductive to the development of physical discipline of statistics and to be more suitable for students.



Standards related to Statistics

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No standards are currently tagged "Statistics"