Stochastic Processes: Estimation, Optimisation and Analysis by Kaddour NajimStochastic Processes: Estimation, Optimisation and Analysis by Kaddour Najim

Stochastic Processes: Estimation, Optimisation and Analysis

byKaddour Najim, Kaddour Najim, Enso Ikonen...

Other | July 1, 2004

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A ‘stochastic’ process is a ‘random’ or ‘conjectural’ process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance.

This book deals with the tools and techniques used in the stochastic process – estimation, optimisation and recursive logarithms – in a form accessible to engineers and which can also be applied to Matlab.

Amongst the themes covered in the chapters are mathematical expectation arising from increasing information patterns, the estimation of probability distribution, the treatment of distribution of real random phenomena (in engineering, economics, biology and medicine etc), and expectation maximisation. The latter part of the book considers optimization algorithms, which can be used, for example, to help in the better utilization of resources, and stochastic approximation algorithms, which can provide prototype models in many practical applications.

* An engineering approach to applied probabilities and statistics
* Presents examples related to practical engineering applications, such as reliability, randomness and use of resources
* Readers with varying interests and mathematical backgrounds will find this book accessible

Title:Stochastic Processes: Estimation, Optimisation and AnalysisFormat:OtherDimensions:305 pages, 1 × 1 × 1 inPublished:July 1, 2004Publisher:Elsevier ScienceLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:008051779X

ISBN - 13:9780080517797


Table of Contents

Stochastic Processes: Foundations of probability; Probability Densities Estimation; Optimisation Techniques; Analysis of Recursive Stochastic Algorithms