Random processes for image and signal processing
Part of the SPIE/IEEE Series on Imaging Science and Engineering. This book provides a framework for understanding the ensemble of temporal, spatial, and higher-dimensional processes in science and engineering that vary randomly in observations. Suitable as a text for undergraduate and graduate students with a strong background in probability and as a graduate text in image processing courses.--Résumé de l'éditeur.
Read More ↓Title Statements
- Full title :Random processes for image and signal processing / Edward R. Dougherty.
Summary
Part of the SPIE/IEEE Series on Imaging Science and Engineering. This book provides a framework for understanding the ensemble of temporal, spatial, and higher-dimensional processes in science and engineering that vary randomly in observations. Suitable as a text for undergraduate and graduate students with a strong background in probability and as a graduate text in image processing courses.--Résumé de l'éditeur.
Read More ↓Edition Statements
- Publication Date:1999.
Publication Statements
- Publisher(s):SPIE
- Place of Publication:Bellingham, Wash
- Language:eng
- Publication Date:1999.
Notes
Titre de l'écran-titre (visionné le 11 mars 2011).
In SPIE digital library.
The Physical Object
- Description:1 texte électronique (xix, 592 p. : illustrations) : : fichiers PDF
Edition Identifiers
- ISBN:9780819478450, 0819478458
- DOI:10.1117/3.268105
- oclc:ocn755947472
- LC Classification:TA1637
- Dewey Decimal:621.382/2/0151923
Table of Contents
Chapter 1. Probability theory -- Probability space -- Events -- Conditional probability -- Random variables -- Probability distributions -- Probability densities -- Functions of a random variable -- Moments -- Expectation and variance -- Moment-generating function -- Important probability distributions -- Binomial distribution -- Poisson distribution -- Normal distribution -- Gamma distribution -- Beta distribution -- Computer simulation -- Multivariate distributions -- Jointly distributed random variables -- Conditioning -- Independence -- Functions of several random variables -- Basic arithmetic functions of two random variables -- Distributions of sums of independent random variables -- Joint distributions of output random variables -- Expectation of a function of several random variables -- Covariance -- Multivariate normal distribution -- Laws of large numbers -- Weak law of large numbers -- Strong law of large numbers -- Central limit theorem -- Parametric estimation via random samples -- Random-sample estimators -- Sample mean and sample variance -- Minimum-variance unbiased estimators -- Method of moments -- Order statistics -- Maximum-likelihood estimation -- Maximum-like…
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