Probability density function

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In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point. (Wikipedia.org)






Conferences related to Probability density function

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2020 IEEE International Conference on Plasma Science (ICOPS)

IEEE International Conference on Plasma Science (ICOPS) is an annual conference coordinated by the Plasma Science and Application Committee (PSAC) of the IEEE Nuclear & Plasma Sciences Society.


2019 IEEE 46th Photovoltaic Specialists Conference (PVSC)

Photovoltaic materials, devices, systems and related science and technology


2019 IEEE 58th Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).


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 Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

The conference is intended to provide an international forum for the exchange of information on state-of-the-art research in antennas, propagation, electromagnetics, and radio science.


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Periodicals related to Probability density function

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


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.


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 Probability density function

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Xplore Articles related to Probability density function

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Keynote III (joint with PPoPP)

2009 IEEE 15th International Symposium on High Performance Computer Architecture, 2009

None


Statistical Analysis of Partial Discharge Data Based on Master Equation

2011 46th International Universities' Power Engineering Conference (UPEC), 2011

In this paper, we apply stochastic master equation (ME) to study the dynamic of probability density function (PDF) in the state space spanned by the PD peak variable and load variable describing the states of the Partial Discharge (PD) process. The states of the PD process are obtained by dividing the state space into several regions. Through studying the frequencies ...


Data Transmission and Integrity

Communication Systems Principles Using MATLAB, None

This chapter distinguishes between error detection and error correction. It shows calculation of the bit error probabilities for a simple channel coding scheme. The chapter helps the reader to understand the working of algorithms for block error detection and block error correction. It explains the operation of convolutional coding, including path‐search algorithms. The chapter discusses private key encryption, key‐exchange methods, ...


Session TA1b: Compressive sensing

2008 42nd Asilomar Conference on Signals, Systems and Computers, 2008

None


RBF networks for density estimation

1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

A non-parametric probability density function (pdf) estimation technique is presented. The estimation consists in approximating the unknown pdf by a network of Gaussian Radial Basis Functions (GRBFs). Complexity analysis is introduced in order to select the optimal number of GRBFs. Results obtained on real data show the potentiality of this technique.


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Educational Resources on Probability density function

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IEEE.tv Videos

Designing Reconfigurable Large-Scale Deep Learning Systems Using Stochastic Computing - Ao Ren: 2016 International Conference on Rebooting Computing
AlGaN/GaN Plasmonic Terahertz Detectors
Micro-Apps 2013: Understanding Probability of Intercept for Intermittent Signals
Advances in MgB2 - ASC-2014 Plenary series - 7 of 13 - Wednesday 2014/8/13
EMBC 2011-Keynote-Kamil Ugurbil-Frontiers in Neuroimaging: from Cortical Columns to Whole Brain Function, Connectivity and Morphology
International Future Energy Challenge (IFEC) 2017
Materials Challenges for Next-Generation, High-Density Magnetic Recording - Kazuhiro Hono: IEEE Magnetics Distinguished Lecture 2016
Introduction: Emerging Technology for Probabilistic Inference - Pierre Bessiere at INC 2019
International Future Energy Challenge 2018
Octopus-Inspired Robot Can Grasp, Crawl and Swim -- IEEE Spectrum Report
IMS 2015: Wearable electronics - why wear it?
Infineon Technologies: Power Efficiency from Generation to Consumption
KeyTalks: The US Department of Energy's Perspective on Achieving Low Cost High Efficiency Energy
Imaging Human Brain Function with Simultaneous EEG-fMRI - IEEE Brain Workshop
How Symmetry Constrains Evolutionary Optimizers: A Black Box Differential Evolution Case Study - IEEE Congress on Evolutionary Computation 2017
Bari-Bari-II: Jack-Up Rescue Robot with Debris Opening Function
Ted Berger: Far Futures Panel - Technologies for Increasing Human Memory - TTM 2018
Multi-Function VCO Chip for Materials Sensing and More - Jens Reinstaedt - RFIC Showcase 2018
Next Generation Power Supplies - APEC 2016
Micro-Apps 2013: Environment Simulation for Counter-IED Jammer Test

IEEE-USA E-Books

  • Keynote III (joint with PPoPP)

    None

  • Statistical Analysis of Partial Discharge Data Based on Master Equation

    In this paper, we apply stochastic master equation (ME) to study the dynamic of probability density function (PDF) in the state space spanned by the PD peak variable and load variable describing the states of the Partial Discharge (PD) process. The states of the PD process are obtained by dividing the state space into several regions. Through studying the frequencies of transitions obtained from the available data, the transition coefficients of the master equations can be estimated. Choice of the number of states depends on the result of the statistics significant test.

  • Data Transmission and Integrity

    This chapter distinguishes between error detection and error correction. It shows calculation of the bit error probabilities for a simple channel coding scheme. The chapter helps the reader to understand the working of algorithms for block error detection and block error correction. It explains the operation of convolutional coding, including path‐search algorithms. The chapter discusses private key encryption, key‐exchange methods, and public‐key encryption. It reviews two useful concepts in modeling data transmission integrity. These are probability concepts and integer arithmetic. Calculations for data transfer integrity checking, and newer approaches to data security and encryption, depend on integer arithmetic in general and modulo arithmetic in particular. The chapter introduces the key concept of the bit error rates and relates it to the system overall, the transmitted signal power, and the external noise encountered.

  • Session TA1b: Compressive sensing

    None

  • RBF networks for density estimation

    A non-parametric probability density function (pdf) estimation technique is presented. The estimation consists in approximating the unknown pdf by a network of Gaussian Radial Basis Functions (GRBFs). Complexity analysis is introduced in order to select the optimal number of GRBFs. Results obtained on real data show the potentiality of this technique.

  • On the sizes of Voronoi cells in entropy-constrained vector quantization

    Voronoi cells for vector quantization subject to an entropy constraint are considered. It is shown that the constraint on the output entropy leads to a weaker and even vanishing dependency of the Voronoi cell's volume on the probability density function. Using some simplifying assumptions like linearization of a small part of the r-dimensional input space and modeling of the cell shapes as hyperspheres leads to an analytic expression of the quotient of the volumes of two neighboring Voronoi cells. The results confirm the use of entropy coded lattice vector quantizers with optimized reproduction vectors in cases of vanishing dependency and may in other cases be exploited for the design of vector companders to be used in conjunction with lattice vector quantization.

  • DBRV Method for Calculation of the ISI Statistic

    This chapter contains sections titled:IntroductionMatrix Method for the Total ISISimulations of ISI PDFConcepts for the Gaussian StatisticDBRV Method for the Total ISIConclusionsReferences

  • Session TP5b: Cognitive systems and spectrum sharing

    None

  • Quantization and Coding

    This chapter discusses principles of scalar quantization and explains the operation of a vector quantization. It explores the principles of minimum‐redundancy code word assignment and provides the important algorithm classes for lossless. The chapter also explains several image compression approaches, including the Discrete Cosine Transform. It helps the reader to understand the basic approach to waveform and parametric speech encoding and then explains the advantages and disadvantages of each. The chapter also explores the key requirements for audio encoders and the building blocks that go to make up an audio encoding system. It reviews some of the notions of probability, which are useful in modeling errors in communication channels, as well as difference equations, which are used extensively in signal encoding. The chapter gives an overview of coding: Image Coding; Source Coding; and Speech and Audio Coding. It also discusses digital channel capacity.

  • Session 11

    Start of the above-titled section of the conference proceedings record.



Standards related to Probability density function

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IEEE Recommended Practice for Determining the Peak Spatial-Average Specific Absorption Rate (SAR) in the Human Head from Wireless Communications Devices: Measurement Techniques

To specify protocols for the measurement of the peak spatial-average specific absorption rate (SAR) in a simplified model of the head of users of hand-held radio transceivers used for personal wireless communications services and intended to be operated while held next to the ear. It applies to contemporary and future devices with the same or similar operational characteristics as contemporary ...


IEEE Standard for Safety Levels With Respect to Human Exposure to Electromagnetic Fields, 0-3 kHz

Develop safety levels for human exposure to electromagnetic fields from 0 to 3kHz. This standard will be based on the results of an evaluation of the relevant scientific literature and proven effects which are well established and for which thresholds of reaction are understood. Field limits will be derived from threshold current densities or internal electric fields.



Jobs related to Probability density function

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