MARC Record from harvard_bibliographic_metadata

LEADER: 04371cam a2200325uu 4500
001 000674888-0
005 20020606090541.3
008 711216s1965 nyua 00000 eng
010 $a 64022956 //r822
035 0 $aocm00527708
040 $aDLC$cDLC$dm.c.$dWQM
050 0 $aQA273$b.P2
060 4 $aQA 273 P218p 1965
082 $a519.1
100 1 $aPapoulis, Athanasios,$d1921-
245 10 $aProbability, random variables, and stochastic processes.
260 0 $aNew York,$bMcGraw-Hill$c[c1965]
300 $axi, 583 p.$billus.$c23 cm.
440 0 $aMcGraw-Hill series in systems science
504 $aIncludes bibliographical references.
505 0 $aProbability and random variables. The meaning of probability: Preliminary remarks ; The various definitions of probability ; Determinism versus probability -- The axioms of probability: Set theory ; Probability space ; Conditional probabilities and independent events ; Summary -- Repeated trials: Combined experiments ; Bernoulli trials ; Asymptotic theorems ; Generalized Bernoulli trials ; Bayes' theorem in statistics -- The concept of a random variable: Random variables, distributions, densities ; Examples of distribution and density functions ; Conditional distributions and densities ; Bayes' theorem in statistics (reexamined) -- Functions of one random variable: The concept of a function of one random variable ; Determination of the distribution and density of y = g(x) ; Applications ; Expected value, dispersion, moments ; Characteristic functions -- Two random variables: Joint distribution and density functions ; Conditional distributions and densities ; Independent random variables ; Jointly normal random variables -- Functions of two random variables: One function of two random variables ; Two functions of two random variables ; Expected value, moments, characteristic functions ; Mean-square estimation, the orthogonality principle ; More on normal random variables -- Sequences of random variables: General concepts ; Mean, mean-square estimation, moments, characteristic functions ; Applications ; Normal random variables ; Convergence concepts and the law of large numbers ; The central-limit theorem.
505 0 $aStochastic processes. General concepts: Introduction remarks ; Special processes ; Definitions ; Stationary processes ; Transformation of stochastic processes (systems) ; Stochastic continuity and differentiation ; Stochastic differential equations ; Stochastic integrals, time averages, ergodicity -- Correlation and power spectrum of stationary processes: Correlation ; Power spectrum ; Linear systems ; Hilbert transforms, shot noise, thermal noise ; Mean-square periodicity and Fourier series ; Band-limited processes ; An estimate of the variation of a band-limited process -- Linear mean-square estimation: Introductory remarks ; The orthogonality principle in linear mean-square estimation ; The Wiener-Kolmogoroff theory ; The filtering problem ; The prediction problem ; Wide-sense Markoff sequences and recursive filtering -- Nonstationary processes; transients in linear systems with stochastic inputs: Transients in linear systems with stochastic inputs ; Two-dimensional Fourier transforms ; Time averages -- Harmonic analysis of stochastic processes: Series expansions ; Approximate Fourier expansion with uncorrelated coefficients ; Fourier transforms of stochastic processes ; Generalized harmonic analysis -- Stationary and nonstationary normal processes: General remarks ; Stationary processes ; Detection ; The zero-crossing problem ; Conditional densities and mean-square estimation ; Bandpass processes ; The Wiener-Levy process -- Brownian movement and Markoff processes: Langevin's equation ; Motion of a harmonically bound particle ; Markoff sequences ; Markoff processes -- Poisson process and shot noise: Poisson distributions ; Random points in time ; Shot noise ; Densities and characteristic functions ; High-density shot noise ; Square-law detection of shot noise.
650 0 $aProbabilities.
650 0 $aRandom variables.
650 0 $aStochastic processes.
650 2 $aProbability.
650 2 $aStochastic Processes.
776 08 $iOnline version:$aPapoulis, Athanasios, 1921-$tProbability, random variables, and stochastic processes.$dNew York, McGraw-Hill [©1965]$w(OCoLC)564362785
988 $a20020608
906 $0DLC