An introduction to probability at the undergraduate level
Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.
Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB® provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics,...
Time Series Analysis and Its Applications presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception...
The twenty-first century has seen a breathtaking expansion of statistical methodology,
both in scope and in influence. “Big data,” “data science,” and “machine learning” have
become familiar terms in the news, as statistical methods are brought to bear upon the
enormous data sets of modern science...
Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book...
This comprehensive book covers the strategy, tactics, and processes needed for successful project portfolio management. It outlines a road map to unprecedented project management improvement and includes a detailed implementation plan for both strategic planning and a PMO that gives you measurable results in weeks. The author delineates four...
In a broad sense, speech dynamics are time-varying or temporal characteristics in all stages
of the human speech communication process. This process, sometimes referred to as speech
chain [1], starts with the formation of a linguistic message in the speaker’s brain and ends with
the arrival of the message in the...
The classical factory fades into history as production plants today develop into modern service centers. Problems in management arise for which many companies are not yet prepared: economic efficiency of modern added value is not a property of products alone but of the process. Decisive potential in business now is a question of process capability,...
This is the first book-length treatment of the Variational Bayes (VB) approximation in signal processing. It has been written as a self-contained, self-learning guide for academic and industrial research groups in signal processing, data analysis, machine learning, identification and control. It reviews the VB distributional approximation, showing...
The development of pattern recognition methods on the basis of so-called Markov
models is tightly coupled to the technological progress in the field of automatic
speech recognition. Today, however, Markov chain and hidden Markov models are
also applied in many other fields where the task is the modeling and analysis of
chronologically...
