Probability distribution

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In probability theory, a probability mass, probability density, or probability distribution is a function that describes the probability of a random variable taking certain values. (Wikipedia.org)






Conferences related to Probability distribution

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2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)

2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC2019) will be held in the south of Europe in Bari, one of the most beautiful and historical cities in Italy. The Bari region’s nickname is “Little California” for its nice weather and Bari's cuisine is one of Italian most traditional , based of local seafood and olive oil. SMC2019 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report up-to-the-minute innovations and developments, summarize state­of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems and cybernetics. Advances have importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience, and thereby improve quality of life.


2019 IEEE International Reliability Physics Symposium (IRPS)

Meeting of academia and research professionals to discuss reliability challenges.


2019 IEEE International Symposium on Information Theory (ISIT)

Information theory and coding theory and their applications in communications and storage, data compression, wireless communications and networks, cryptography and security, information theory and statistics, detection and estimation, signal processing, big data analytics, pattern recognition and learning, compressive sensing and sparsity, complexity and computation theory, Shannon theory, quantum information and coding theory, emerging applications of information theory, information theory in biology.


2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

This conference is the annual premier meeting on the use of instrumentation in the Nuclear and Medical fields. The meeting has a very long history of providing an exciting venue for scientists to present their latest advances, exchange ideas, renew existing collaboration and form new ones. The NSS portion of the conference is an ideal forum for scientists and engineers in the field of Nuclear Science, radiation instrumentation, software engineering and data acquisition. The MIC is one of the most informative venues on the state-of-the art use of physics, engineering, and mathematics in Nuclear Medicine and related imaging modalities, such as CT and increasingly so MRI, through the development of hybrid devices


2019 IEEE Power & Energy Society General Meeting (PESGM)

The Annual IEEE PES General Meeting will bring together over 2900 attendees for technical sessions, administrative sessions, super sessions, poster sessions, student programs, awards ceremonies, committee meetings, tutorials and more


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Periodicals related to Probability distribution

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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.


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 ...


Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


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Most published Xplore authors for Probability distribution

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Xplore Articles related to Probability distribution

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A Note on the Word Error Probability Associated with a Sequence of Digits Having Unequal Error Probabilities

[{u'author_order': 1, u'affiliation': u'Tech-Center Div., Cook Electric Co., Morton Grove, Ill', u'full_name': u'F. Splitt'}] IEEE Transactions on Communications Systems, 1963

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The Emitter-Coupled Differential Amplifier

[{u'author_order': 1, u'full_name': u'D. Slaughter'}] IRE Transactions on Circuit Theory, 1956

The transistor emitter-coupled differential amplifier is analogous to the cathode-coupled differential amplifier and gives promise of excellent utility in transistorized circuitry. Expressions are given for 1) the circuit voltage gain, current gain, and input impedance, 2) the common-mode rejection when the circuit is used as a differencing amplifier, and 3) the signal unbalance when the circuit is employed as a ...


Scintillation caused by the ionosphere with non-Gaussian statistics of irregularities

[{u'author_order': 1, u'affiliation': u'Space Research Centre, Polish Academy of Science, Warsaw, Poland.', u'full_name': u'A. W. Wernik'}, {u'author_order': 2, u'affiliation': u'Space Research Centre, Polish Academy of Science, Warsaw, Poland.', u'full_name': u'M. Grzesiak'}] Radio Science, 2011

In situ measurements indicate that the probability distribution function (pdf) of plasma density fluctuations on scales of importance to scintillation is far from the Gaussian and resemble the Laplace (double exponential) distribution. Radio wave propagation in the ionosphere with irregularities subject to the Gaussian and Laplace pdf has been modeled using the multiple two-dimensional phase screen method. The Chapman altitude ...


An Investigation on Mutual Information for the Linear Predictive System and the Extrapolation of Speech Signals

[{u'author_order': 1, u'full_name': u'Jalal Taghia'}, {u'author_order': 2, u'full_name': u'Rainer Martin'}, {u'author_order': 3, u'full_name': u'Jalil Taghia'}, {u'author_order': 4, u'full_name': u'Arne Leijon'}] Speech Communication; 10. ITG Symposium, 2012

Mutual information (MI) is an important information theoretic concept which has many applications in telecommunications, in blind source separation, and in machine learning. More recently, it has been also employed for the instrumental assessment of speech intelligibility where traditionally correlation based measures are used. In this paper, we address the difference between MI and correlation from the viewpoint of discovering ...


A criterion for the diagonal expansion of a second-order probability distribution in orthogonal polynomials

[{u'author_order': 1, u'affiliation': u'Ordnance Res. Lab., Pennsylvania State University, University Park, Pa.', u'full_name': u'John L. Brown'}] IRE Transactions on Information Theory, 1958

In a recent paper,<sup>1</sup> Barrett and Lampard introduced an expansion for second-order probability distributions which expresses such a distribution as a double series involving orthogonal polynomials associated with the corresponding first-order probability distributions. Several interesting consequences were derived for the class, A, consisting of all second-order distributions having a diagonal expansion of the form


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Educational Resources on Probability distribution

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eLearning

No eLearning Articles are currently tagged "Probability distribution"

IEEE-USA E-Books

  • Probability Theory

    The reason why many wireless communication books start from probability theory is that wireless communications deal with uncertainty. If there are no channel impairments by nature, we can receive the transmitted messages without any distortion and do not need to care about probability theory. A random signal cannot be predicted but we may forecast future values from previous events using probability theory. When we consider a signal over time, we find the energy spectral density (ESD) and power spectral density (PSD). A correlation function is used to know the relationship between random variables. When we face a noise that the nature has made electrical component noises or thermal noises, we assume it follows Gaussian distribution because of central limit theorems. This theorem means that the sample average and sum have Gaussian distribution regardless of distribution of each random variable.

  • Input Modeling and Output Analysis

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  • Statistical Distributions and Random Number Generation

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  • Discrete Probability Theory

    This chapter contains sections titled:The Origins of Probability TheoryChance Experiments, Sample Points, Spaces, and EventsRandom VariablesMoments—Expectation and VarianceThe Birthday ParadoxConditional Probability and IndependenceThe Law of Large Numbers (LLN)The Central Limit Theorem (CLT)Random Processes and Markov Chains

  • Estimating Reliability Parameters

    For our model to be as accurate as possible, we require?>good?> estimates of reli¬ability parameters. Without any data related to the system we are designing, expert opinions of reliability engineers and analysts are used. These experts will usually base their estimates on reliability data similar projects, systems, or components. Vendors may provide some reliability data as well. If we have test data from the system being built, or better yet, data from deployed systems, we use that information to update our estimates. Monte Carlo simulations are also helpful for our estimation. A powerful technique is the use of Bayes's theorem, which provides a method for combining previous estimates with new data to create a new estimate that com¬bines both.

  • Optimum Hashing

    This chapter contains sections titled:The Ullman–Yao FrameworkThe Rates at Which a Cell is Probed and OccupiedPartitions of(_i_)Scenarios,(_i_)Subscenarios, and Their SkeletonsRandomly Generated_m_‐ScenariosBounds on Random SumsCompleting the Proof of Theorem 15.1

  • Recurrence and Generating Functions

    This chapter contains sections titled:RecursionsGenerating FunctionsLinear Constant Coefficient RecursionsSolving Homogeneous LCCRs Using Generating FunctionsThe Catalan RecursionThe Umbral CalculusExponential Generating FunctionsPartitions of a Set: The Bell and Stirling NumbersRouché's Theorem and the Lagrange's Inversion Formula

  • Closed Queueing Networks

    This chapter contains sections titled:Jackson Closed Queueing NetworksSteady‐state Probability DistributionConvolution AlgorithmPerformance MeasuresMean Value AnalysisApplication of Closed Queueing NetworksProblems

  • Random Processes

    In this chapter, some of the basic notions and mathematical models of statistical and deterministic mechanics are combined into a stochastic system model, which represents the evolution over time of key statistical parameters in systems with uncertain dynamics. These stochastic system models are used to define random processes (RPs) in continuous time and in discrete time (also called random sequences). They represent the state of knowledge about a dynamic system-including its state of uncertainty. They also represent what we know about a dynamic system, including a quantitative model for what we do not know. Properties of uncertain dynamic systems are characterized by statistical parameters such as_means_,_correlations_, and_covariances_. By using only these numerical parameters, one can obtain finite representations of some probability distributions, which is important for implementing the solution on digital computers.

  • Monte Carlo Simulation

    Monte Carlo simulation consists of imitating the stochastic behavior of a physical system. Monte Carlo simulation is often used as an alternative to analytical methods. Basic concepts of Monte Carlo simulation applied to power systems are described using an example of a system with two independent components. Random sampling, or nonsequential simulation, consists of performing random sampling over the aggregate of all possible states the system can assume during the period of interest. In sequential methods, the mathematical model of the system is made to generate an artificial history over time, and appropriate statistical inferences are drawn from this history. It is crucial to sample sufficient number of states to estimate reliability indices. The chapter describes the estimation and convergence criterion of both techniques, namely: random sampling and sequential sampling. It explains variance reduction techniques, such as importance sampling, control variate sampling, antithetic variate sampling, and Latin Hypercube Sampling (LHS).



Standards related to Probability distribution

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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 ...



Jobs related to Probability distribution

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