Modeling is practiced in engineering and all physical sciences. Many specialized texts exist - written at a high level - that cover this subject. However, students and even professionals often experience difficulties in setting up and solving even the simplest of models. This can be attributed to three difficulties: the proper choice of model,...
With the advent of sophisticated general programming environments like Mathematica, the task of developing new models of metabolism and visualizing their responses has become accessible to students of biochemistry and the life sciences in general. Modelling Metabolism with Mathematica presents the approaches, methods, tools, and algorithms...
Previously known as Statistical Methods for Health Sciences, this bestselling resource is one of the first books to discuss the methodologies used for the analysis of clustered and correlated data. While the fundamental objectives of its predecessors remain the same, Analysis of Correlated Data with SAS and R, Third Edition incorporates...
A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundationsof Statistical Algorithms: With References to R Packages reviews the historical development of basic algorithms to illuminate the evolution of today’s more powerful statistical...
Thoroughly classroom-tested and proven to be a valuable self-study companion, Linear Control System Analysis and Design: Sixth Edition provides an intensive overview of modern control theory and conventional control system design using in-depth explanations, diagrams, calculations, and tables.
Avoiding heavy mathematics and lengthy programming details, Digital Image Processing: An Algorithmic Approach with MATLAB® presents an easy methodology for learning the fundamentals of image processing. The book applies the algorithms using MATLAB®, without bogging down...
Reveals How HMMs Can Be Used as General-Purpose Time Series Models
Implements all methods in R Hidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, circular, and...
Bringing together computational research tools in one accessible source, Reproducible Research with R and RStudio guides you in creating dynamic and highly reproducible research. Suitable for researchers in any quantitative empirical discipline, it presents practical tools for data collection, data analysis, and the...
Computer-Aided Control Systems Design: Practical Applications Using MATLAB® and Simulink® supplies a solid foundation in applied control to help you bridge the gap between control theory and its real-world applications. Working from basic principles, the book delves into control systems...
"…There are many good textbooks today to teach digital signal processing, but most of them are content to teach the theory, and perhaps some MATLAB® simulations. This book has taken a bold step forward. It not only presents the theory, it reinforces...
Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.
Numerous Useful Examples, Problems, and Solutions – An Extensive and...
This textbook introduces several major numerical methods for solving various partial differential equations (PDEs) in science and engineering, including elliptic, parabolic, and hyperbolic equations. It covers traditional techniques that include the classic finite difference method and the finite element method as well as...
