Maths for computer scientists

Finite Element Methods are used for numerous engineering applications where numerical solutions of partial differential equations are needed.

The last 15 years have seen an explosion of interest in wavelets with applications in fields such as image compression, turbulence, human vision, radar and earthquake prediction.

Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation.

Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods.

"e;Information Theory and Statistical Learning"e; presents theoretical and practical results about information theoretic methods used in the context of statistical learning.

This book gives you a step-by-step introduction to analysing time series using the open source software R.

Monte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve a wide range of scientific and engineering problems.

While we were busy putting together the present collection of articles celebrating the twentieth birthday of our journal, Discrete & Computational Geometry, and, in a way, of the ?

Programming Languages: An Active Learning Approach introduces students to three programming paradigms: object-oriented/imperative languages using C++ and Ruby, functional languages using Standard ML, and logic programming using Prolog.

This book will be a valuable reference for researchers in the eare of nonparametrics.

Optimization is a field important in its own right but is also integral to numerous applied sciences, including operations research, management science, economics, finance and all branches of mathematics-oriented engineering.

This second edition presents up-to-date material on the theory of weak convergance of convolution products of probability measures in semigroups, the theory of random walks on semigroups, and their applications to products of random matrices.

The Primality Testing Problem (PTP) has now proved to be solvable in deterministic polynomial-time (P) by the AKS (Agrawal-Kayal-Saxena) algorithm, whereas the Integer Factorization Problem (IFP) still remains unsolvable in (P).

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical.

In this monograph, new combinatorial and computational approaches in the study of RNA structures are presented which enhance both mathematics and computational biology.

It's hard to believe that it's been over a decade since One Jump Ahead: Challenging Human Supremacy at Checkers was published.

Recent Advances in Numerical Methods features contributions from distinguished researchers focused on significant aspects of current numerical methods and computational mathematics.

The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics.

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics.

The main intended audience for this book is undergraduate students in pure and applied sciences, especially those in engineering.

Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty.

Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory.

Performance optimization is vital in the design and operation of modern engineering systems, including communications, manufacturing, robotics, and logistics.

The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.

Practical Optimization: Algorithms and Engineering Applications provides a hands-on treatment of the subject of optimization.

Gluecklich, die wissen, dass hinter allen Sprachen das Unsaegliche steht.

Introduction to Discrete Event Systems is a comprehensive introduction to the field of discrete event systems, offering a breadth of coverage that makes the material accessible to readers of varied backgrounds.

Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty.

Sequential Dynamical Systems (SDS) are a class of discrete dynamical systems which significantly generalize many aspects of systems such as cellular automata, and provide a framework for studying dynamical processes over graphs.

Essential Mathematica: With Applications to Mathematics and Physics, based on the lecture notes of a course taught at the University of Illinois at Chicago to advanced undergrad and graduate students, teaches how to use Mathematica to solve a wide variety problems in mathematics and physics.

Modern computer algebra systems are revolutionizing the teaching and learning of mathematically intensive subjects in science and engineering, enabling students to explore increasingly complex and computationally intensive models that provide analytic solutions, animated numerical solutions, and complex two- and three-dimensional graphic displays.

Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets.

During the last decade, the area of stochastic max-plus linear systems has witnessed a rapid development, which created a growing interest in this area.

After that, it was down to attitude.

Integrated Methods for Optimization integrates the key concepts of Mathematical Programming and Constraint Programming into a unified framework that allows them to be generalized and combined.

Multivariate public key cryptosystems (MPKC) is a fast-developing new area in cryptography.

Modern apparatuses allow us to collect samples of functional data, mainly curves but also images.

Generic programming is about making programs more adaptable by making them more general.

The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains.

The primary reason for producing this book is to demonstrate and commu- nicate the pervasive nature of Discrete Optimisation.

A classical queueing model consists of three parts - arrival process, service process, and queue discipline.

We publish in this volume a selection of the papers presented at the 22nd Conference on System Modeling and Optimization, held at the Politecnico di Torino in July 2005.

We publish in this volume the plenary talks and a selection of the papers on numerics, optimization and their applications, presented at the 22nd Conference on System Modeling and Optimization, held at the Politecnico di Torino in July 2005.

It is not an exaggeration that much of what people devote in their hfe re- solves around optimization in one way or another.

Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time.

Space, structure, and randomness: these are the three key concepts underlying Georges Matheron's scientific work.

Computer algebra systems are revolutionizing the teaching, the learning, and the exploration of science.

Mathematical Problems from Applied Logic I presents chapters from selected, world renowned, logicians.