1992, 20

Book

1983, Volume no. 19., iv, 87

Book

1983, Computer science monographs, Volume no. 19-20, 2 v.

Book

Applied Energy, ISSN 0306-2619, 2011, Volume 88, Issue 5, pp. 1848 - 1856

In addition to the probability density function (pdf) derived with maximum entropy principle (MEP), several kinds of mixture probability functions have already...

Statistical error | Probability density function | Weibull function | Mixture function | Wind speed | Wind power density | STATISTICS | ENERGY & FUELS | PARAMETERS | REGION | DISTRIBUTIONS | ENGINEERING, CHEMICAL | RESOURCE ASSESSMENT | DISTRIBUTION MODELS | MAXIMUM-ENTROPY PRINCIPLE | SPEED DISTRIBUTION | Wind speed Wind power density Probability density function Weibull function Mixture function Statistical error | Errors | Energy use | Kolmogorov-Smirnov test | Neural networks | Wind power generation | Density | Probability density functions

Statistical error | Probability density function | Weibull function | Mixture function | Wind speed | Wind power density | STATISTICS | ENERGY & FUELS | PARAMETERS | REGION | DISTRIBUTIONS | ENGINEERING, CHEMICAL | RESOURCE ASSESSMENT | DISTRIBUTION MODELS | MAXIMUM-ENTROPY PRINCIPLE | SPEED DISTRIBUTION | Wind speed Wind power density Probability density function Weibull function Mixture function Statistical error | Errors | Energy use | Kolmogorov-Smirnov test | Neural networks | Wind power generation | Density | Probability density functions

Journal Article

Progress in Energy and Combustion Science, ISSN 0360-1285, 2010, Volume 36, Issue 2, pp. 168 - 259

Probability density function (PDF) methods offer compelling advantages for modeling chemically reacting turbulent flows. In particular, they provide an elegant...

Filtered density function method | Turbulent combustion modeling | Probability density function method | ENERGY & FUELS | JET DIFFUSION FLAME | FINITE-RATE CHEMISTRY | VITIATED CO-FLOW | ENGINEERING, MECHANICAL | ENGINEERING, CHEMICAL | DIRECT NUMERICAL-SIMULATION | THERMODYNAMICS | LARGE-EDDY SIMULATION | STOCHASTIC LAGRANGIAN MODELS | BLUFF-BODY FLAMES | COMPUTATIONAL FLUID-DYNAMICS | MONTE-CARLO-SIMULATION | TRANSPORTED SCALAR PDF | Combustion | Algorithms | Mechanical engineering | Analysis | Methods | Radiation | Turbulence | Computational fluid dynamics | Mathematical analysis | Portable document format | Mathematical models | Probability density functions

Filtered density function method | Turbulent combustion modeling | Probability density function method | ENERGY & FUELS | JET DIFFUSION FLAME | FINITE-RATE CHEMISTRY | VITIATED CO-FLOW | ENGINEERING, MECHANICAL | ENGINEERING, CHEMICAL | DIRECT NUMERICAL-SIMULATION | THERMODYNAMICS | LARGE-EDDY SIMULATION | STOCHASTIC LAGRANGIAN MODELS | BLUFF-BODY FLAMES | COMPUTATIONAL FLUID-DYNAMICS | MONTE-CARLO-SIMULATION | TRANSPORTED SCALAR PDF | Combustion | Algorithms | Mechanical engineering | Analysis | Methods | Radiation | Turbulence | Computational fluid dynamics | Mathematical analysis | Portable document format | Mathematical models | Probability density functions

Journal Article

1984, Volume no. 20., 199

Book

1977, ISBN 0470150173, 308

Book

1961, Mathematical tables, Volume 16., 129

Book

INTELLIGENT DATA ANALYSIS, ISSN 1088-467X, 2019, Volume 23, Issue 2, pp. 385 - 405

This study establishes the new results for Cluster Width of probability Density functions (CWD). There are the upper and lower bounds of CWD and the...

density | distance | width | Cluster | CLASSIFICATION | fuzzy | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Cluster analysis | Lower bounds | Algorithms | Statistical analysis | Mathematical analysis | Probability density functions

density | distance | width | Cluster | CLASSIFICATION | fuzzy | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Cluster analysis | Lower bounds | Algorithms | Statistical analysis | Mathematical analysis | Probability density functions

Journal Article

1980, ISBN 3181423092, Volume Nr. 23., 52

Book

11.
Full Text
Time series classification via divergence measures between probability density functions

Pattern Recognition Letters, ISSN 0167-8655, 07/2019, Volume 125, pp. 42 - 48

In this work, we describe a new method for time series classification (TSC) that consists of modeling time series as probability density functions (PDFs) and...

Kernel methods | Kernel density estimation | Time series classification | Time delay embedding | MODELS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | HEARTBEAT CLASSIFICATION | Computer science | Distribution (Probability theory) | Algorithms | Specific gravity | Analysis

Kernel methods | Kernel density estimation | Time series classification | Time delay embedding | MODELS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | HEARTBEAT CLASSIFICATION | Computer science | Distribution (Probability theory) | Algorithms | Specific gravity | Analysis

Journal Article

IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 07/2017, Volume 39, Issue 7, pp. 1294 - 1308

Parametric maximum likelihood (ML) estimators of probability density functions (pdfs) are widely used today because they are efficient to compute and have...

Maximum likelihood estimation | Computational modeling | density | nonparametric | tail estimation | Convergence | estimation | neuronal receptive fields | pdf | Probability density function | Random variables | Maximum likelihood | Kernel | FIELDS | DRIVEN | BANDWIDTH SELECTION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Distribution (Probability theory) | Kernel functions | Maximum likelihood estimates (Statistics) | Economic models | State of the art | Computer simulation | Maximum likelihood estimators | Regression analysis | Normality | Parameterization | Probability density functions | Complexity

Maximum likelihood estimation | Computational modeling | density | nonparametric | tail estimation | Convergence | estimation | neuronal receptive fields | pdf | Probability density function | Random variables | Maximum likelihood | Kernel | FIELDS | DRIVEN | BANDWIDTH SELECTION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Distribution (Probability theory) | Kernel functions | Maximum likelihood estimates (Statistics) | Economic models | State of the art | Computer simulation | Maximum likelihood estimators | Regression analysis | Normality | Parameterization | Probability density functions | Complexity

Journal Article

Journal of Applied Statistics, ISSN 0266-4763, 03/2017, Volume 44, Issue 4, pp. 583 - 601

Basing on L 1 -distance and representing element of cluster, the article proposes new three algorithms in Fuzzy Clustering of probability density Functions...

clustering | Fuzzy | distance | density function | hierarchical approach | ALGORITHM | CLASSIFICATION | STATISTICS & PROBABILITY | VALIDITY | Databases | Algorithms | Clusters | Clustering | Texture | Probability density functions | Matlab

clustering | Fuzzy | distance | density function | hierarchical approach | ALGORITHM | CLASSIFICATION | STATISTICS & PROBABILITY | VALIDITY | Databases | Algorithms | Clusters | Clustering | Texture | Probability density functions | Matlab

Journal Article

14.
Full Text
EMD-Based Filtering Using Similarity Measure Between Probability Density Functions of IMFs

IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, 01/2014, Volume 63, Issue 1, pp. 27 - 34

This paper introduces a new signal-filtering, which combines the empirical mode decomposition (EMD) and a similarity measure. A noisy signal is adaptively...

similarity measure | Density measurement | probability density function (pdf) | Noise measurement | Indexes | empirical mode decomposition (EMD) | signal filtering | intrinsic mode function (IMF) | Probability density function | Consecutive mean squared error (CMSE) | Pollution measurement | High definition video | Signal to noise ratio | SERIES | ALGORITHM | ENGINEERING, ELECTRICAL & ELECTRONIC | INSTRUMENTS & INSTRUMENTATION | EMPIRICAL MODE DECOMPOSITION | FREQUENCY | UNCERTAINTY | Signal processing | Distribution (Probability theory) | Research | Analysis | Signal and Image Processing | Computer Science

similarity measure | Density measurement | probability density function (pdf) | Noise measurement | Indexes | empirical mode decomposition (EMD) | signal filtering | intrinsic mode function (IMF) | Probability density function | Consecutive mean squared error (CMSE) | Pollution measurement | High definition video | Signal to noise ratio | SERIES | ALGORITHM | ENGINEERING, ELECTRICAL & ELECTRONIC | INSTRUMENTS & INSTRUMENTATION | EMPIRICAL MODE DECOMPOSITION | FREQUENCY | UNCERTAINTY | Signal processing | Distribution (Probability theory) | Research | Analysis | Signal and Image Processing | Computer Science

Journal Article

Nuclear Physics, Section B, ISSN 0550-3213, 05/2018, Volume 930, pp. 384 - 398

The implications of the anarchy principle on CP violation in the lepton sector are investigated. A systematic method is introduced to compute the probability...

QUARK | MATRICES | NONCONSERVATION | ANARCHY | PHYSICS, PARTICLES & FIELDS | Distribution (Probability theory) | Physics - High Energy Physics - Phenomenology | Nuclear and particle physics. Atomic energy. Radioactivity | High Energy Physics - Phenomenology

QUARK | MATRICES | NONCONSERVATION | ANARCHY | PHYSICS, PARTICLES & FIELDS | Distribution (Probability theory) | Physics - High Energy Physics - Phenomenology | Nuclear and particle physics. Atomic energy. Radioactivity | High Energy Physics - Phenomenology

Journal Article

Journal of Computational Physics, ISSN 0021-9991, 05/2017, Volume 336, pp. 627 - 643

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we...

Probability density function | Continuation of fixed points | Stochastic dynamical systems | Lyapunov equation | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MODELS | DYNAMICAL-SYSTEMS | RATIONAL KRYLOV SUBSPACES | ALGORITHM | EQUATIONS | PHYSICS, MATHEMATICAL | Computer science | Marine geography | Atmospheric research | Distribution (Probability theory) | Ocean circulation | Differential equations | Fixed points (mathematics) | Partial differential equations | Computational fluid dynamics | Approximations | Fluid flow | Innovations | Probability | Bifurcation theory | Oceanography | Iterative methods | Probability density functions | Ocean currents | FLUIDS | INSTABILITY | STOCHASTIC PROCESSES | CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS | APPROXIMATIONS | NOISE | MATHEMATICAL SOLUTIONS | PROBABILITY | PROBABILITY DENSITY FUNCTIONS | PARTIAL DIFFERENTIAL EQUATIONS | OCEANOGRAPHY | STEADY-STATE CONDITIONS | FLUID FLOW | ITERATIVE METHODS | BIFURCATION | LYAPUNOV METHOD

Probability density function | Continuation of fixed points | Stochastic dynamical systems | Lyapunov equation | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MODELS | DYNAMICAL-SYSTEMS | RATIONAL KRYLOV SUBSPACES | ALGORITHM | EQUATIONS | PHYSICS, MATHEMATICAL | Computer science | Marine geography | Atmospheric research | Distribution (Probability theory) | Ocean circulation | Differential equations | Fixed points (mathematics) | Partial differential equations | Computational fluid dynamics | Approximations | Fluid flow | Innovations | Probability | Bifurcation theory | Oceanography | Iterative methods | Probability density functions | Ocean currents | FLUIDS | INSTABILITY | STOCHASTIC PROCESSES | CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS | APPROXIMATIONS | NOISE | MATHEMATICAL SOLUTIONS | PROBABILITY | PROBABILITY DENSITY FUNCTIONS | PARTIAL DIFFERENTIAL EQUATIONS | OCEANOGRAPHY | STEADY-STATE CONDITIONS | FLUID FLOW | ITERATIVE METHODS | BIFURCATION | LYAPUNOV METHOD

Journal Article

Optics Communications, ISSN 0030-4018, 10/2017, Volume 400, pp. 1 - 8

The single-point probability density functions (PDF) of the instantaneous Stokes parameters of a polarized plane-wave light field scattered from a...

Probability density function | Stokes parameters | Polarization | Weak scattering | Random medium | FIELDS | INTENSITY FLUCTUATIONS | STATISTICS | LIGHT | SCINTILLATION | QUASI-HOMOGENEOUS SOURCES | WAVES | RANDOM ELECTROMAGNETIC BEAMS | MEDIA | OPTICS | PROPAGATION | Distribution (Probability theory)

Probability density function | Stokes parameters | Polarization | Weak scattering | Random medium | FIELDS | INTENSITY FLUCTUATIONS | STATISTICS | LIGHT | SCINTILLATION | QUASI-HOMOGENEOUS SOURCES | WAVES | RANDOM ELECTROMAGNETIC BEAMS | MEDIA | OPTICS | PROPAGATION | Distribution (Probability theory)

Journal Article