Maths for Scientists

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational...

This book is an introduction to nonlinear programming. It deals with the theoretical foundations and solution methods, beginning with the classical...

The theory of distributions has numerous applications and is extensively used in mathematics, physics and engineering. There is however relatively ...

Through its inclusion of specific applications, The Mathematical Theory of Elasticity, Second Edition continues to provide a bridge between the the...

Mathematician and popular science author Eugenia Cheng is on a mission to show you that mathematics can be flexible, creative, and visual. This joy...

An essential tool made transparent: this book explains the theory behind current numerical methods and shows how to use them in a step-by-step fash...

Biostatistics from Scratch is an accessible, student-friendly introduction to the key statistical techniques used within the biological and environ...

Biostatistics from Scratch is an accessible, student-friendly introduction to the key statistical techniques used within the biological and environ...

Statistical analysis allows us to attach meaning to data that we have collected; it helps us to understand what experimental results really mean, a...

There has been a tremendous increase in the breadth of application of Bayesian methods to problems in industry in the last twenty or so years. Howe...

Prepare students for success in using applied mathematics for engineering practice and post-graduate studies Moves from one mathematical method to...

Table of contents: Stochastic methods in nonlinear structural dynamics.- Stochastic models of uncertainties in computational structural dynamics an...

The Monte Carlo method, largely the brainchild of Stanislaw Ulam and first implemented by John von Neumann, depends upon the use of digital compute...

Artificial Boundary Method systematically introduces the artificial boundary method for the numerical solutions of partial differential equations i...

The book presents the state of the art in high performance computing and simulation on modern supercomputer architectures. It covers trends in hard...

The goal of Algorithmic Mathematics in Machine Learning is to explore several well-known machine learning and data analysis algorithms from a mathe...

Covers multivariable calculus, starting from the basics and leading up to the three theorems of Green, Gauss, and Stokes, but always with an eye on...

The papers in this volume start with a description of the construction of reduced models through a review of Proper Orthogonal Decomposition (POD) ...

Calculations in Chemistry is intended to help students overcome the challenges associated with solving numerical problems in chemistry. Chemistry i...