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Measure theory.
概要
作品:
78 作品在 41 項出版品 41 種語言
書目資訊
Probability and measure /
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An introduction to measure and probability /
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Measures and probabilities /
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Integral, probability, and fractal measures /
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Weak convergence of measures :applications in probability /
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Measure theory /
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Measure theory /
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Real analysis /
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A first look at rigorous probability theory /
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A user's guide to measure theoretic probability /
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Lebesgue measure and integration :an introduction /
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Measure, integral and probability /
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Measures with symmetry properties /
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Measure theory and probability /
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Lebesgue integration on Euclidean space /
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Real analysis :measure theory, integration, and Hilbert spaces /
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Measure and integral :an introduction to real analysis /
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Real analysis :theory of measure and integration /
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Measures, integrals and martingales /
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A first look at rigorous probability theory /
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Measure, Topology, and Fractal Geometry /
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Weak convergence of measures: applications in probability
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Gradient flows in metric spaces and in the space of probability measures /
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Measure, integral and probability /
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Measure theory and probability /
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Measure theory and probability theory /
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Measures with symmetry properties
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Tame geometry with application in smooth analysis
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Measure theory and fine properties of functions /
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Measure theory and integration /
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Integration and modern analysis
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(書目-電子資源)
Measure and integrationan advanced course in basic procedures and applications /
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Probability, random processes, and ergodic properties
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Generalized measure theory
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Essentials of integration theory for analysis
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Measure and integration :a concise introduction to real analysis /
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Topics in measure theory and real analysis
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Measure and integrationpublications 1997-2011 /
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The Borel-Cantelli Lemma
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Handbook of measure theory
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The elements of Cantor sets :with applications /
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A basic course in measure and probability :theory for applications /
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A course on integration theoryincluding more than 150 exercises with detailed answers /
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The elements of Cantor setswith applications /
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Measure and integral :an introduction to real analysis /
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Measure theory and fine properties of functions /
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Repeated measurements and cross-over designs /
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An introduction to measure-theoretic probability
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Measure and Integral
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Essentials of measure theory
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Probability and measure /
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The elements of integration and Lebesgue measure /
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Measure and integration
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Fundamentals of functional analysis
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Analysisfrom concepts to applications /
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Applications of measure theory to statistics
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Measure theory and functional analysis /
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Measure theory and filtering :introduction and applications /
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Analysis on Gaussian spaces
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Measures, integrals and martingales /
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A basic course in measure and probabilitytheory for applications /
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Universal measurementshow to free three birds in one move /
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Repeated measurements and cross-over designs
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Probability and conditional expectationfundamentals for the empirical sciences /
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A course in functional analysis and measure theory
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A concise introduction to measure theory
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Measure and integration
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Density evolution under delayed dynamicsan open problem /
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Essentials of integration theory for analysis
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Measure, integration and a primer on probability theory.Volume 1
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Probability theory :a comprehensive course /
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Classical and discrete functional analysis with measure theory
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Combined measure and shift invariance theory of time scales and applications
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Notes on real analysis and measure theoryfine properties of real sets and functions /
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Measure theory, probability, and stochastic processes
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Regular non-additive multimeasuresfundaments and applications /
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Measure theory and integration
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Measure-theoretic calculus in abstract spaceson the playground of infinite-dimensional spaces /
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更多
較少的
主題
Probability measures.
Maattheorie.
Topology.
Arithmetical algebraic geometry.
Communications Engineering, Networks.
Signal, Image and Speech Processing.
Mathematical Logic and Foundations.
Kalman filtering.
Measure algebras.
Evolution equations, Nonlinear.
Probability Theory and Stochastic Processes.
Smoothing (Numerical analysis)
Cantor, George,
Operator Theory.
Applications of Mathematics.
Distribution (Probability theory)
Calculus.
Differential equations.
Differential Equations.
Stochastic Processes.
Fractals.
Real Functions.
Statistical Theory and Methods.
Operator theory.
Delay differential equations.
Engineering Mathematics.
Control and Systems Theory.
Hilbertruimten.
Lp spaces.
Integrals.
Martingales (Mathematics)
Mathematics.
Integration, Functional.
Functions of a Complex Variable.
Analysis.
Measure theory
Random variables.
Vibration, Dynamical Systems, Control.
Mathematical physics.
Functions of real variables.
Integrals, Generalized.
Dynamical Systems and Ergodic Theory.
Coding and Information Theory.
Cantor sets.
Functional Analysis.
Gaussian measures.
Vibration.
Fourier Analysis.
Probability Theory.
Mathematical and Computational Engineering Applications.
Probabilities.
Mathematical analysis.
Systems Theory, Control.
Partial Differential Equations.
Mathematical Physics.
Dynamics.
Fourier analysis.
Functional analysis.
Lebesgue integral.
Set functions.
Measure and Integration.
Monotone operators.
Differential Geometry.
Stochastic processes.
Engineering.
Statistics.
Integrals, Generalized
Spaces of measures.
Measurement.
Electronic books.
Automatic control.
Measure theory.
Metric spaces.
Convergence.
Geometry.
Differential equations, Partial.
Mathematical statistics.
Statistics
Gaussian distribution.
Ergodic theory.
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