Stochastic Processes
Estimation, Optimisation and Analysis

The foundations of applied statistics and probability for engineers involved with modelling, control and reliability

Kaddour Najim (Author), Enso Ikonen (Author), Ait-Kadi Daoud (Author)

9781903996553, Elsevier Science

Hardback, published 1 July 2004

305 pages
23.4 x 15.6 x 2.3 cm, 0.66 kg

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.

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

Subject Areas: Stochastics [PBWL]