Computer

Computing is an exact science and the systematic study of any aspect necessarily involves the use of mathematical models. Moreover, the rate at which the subject is evolving demands a facility for developing new mathematical systems to keep pace with new computing systems and this requires an appreciation of how mathematics works. An understanding of the underlying mathematical structure facilitates the construction of suitable computer programs to perform computations. Assuming no specific knowledge of mathematics, the authors describe all the basic concepts required and progress from sets (rather than numbers) through a variety of algebraic structures that permit the precise description, specification and subsequent analysis of many problems in computing. The material included provides the essential mathematical foundations for core topics of computer science and extends into the areas of language theory, abstract machine theory and computer geometry. Computer Mathematics will be of

This book is revised and expanded version of the original German text. The arrangement of the material and the structure are essentially unchanged. All remarks in the Preface to the German Edition reg

To perform computer simulation successfully, two rather different sets of skills are required. One of these relates to programming: a simulation program should do what its author intends and do it efficiently. The other is concerned with the collection and analysis of data: statistical tools have to be used in order to obtain with a minimum of effort, accurate and reliable estimates for the desired performance measures. Dr Mitrani covers both of these aspects of the simulation method. The important topics of point and interval estimation, simulation efficiency and the analysis of simulation experiments are discussed in detail. This book, first published in 1982, will be useful to both undergraduate and postgraduate students taking courses on simulation in departments of computer science, operations research and statistics in universities and polytechnics. It will be of benefit also to practitioners in the field.

By the time students have done some programming in one or two languages and have learnt the common ways of representing information in a computer, they will want to embark upon further study of theoretical or applied topics in computer science. Most will encounter problems that require for their solution one or more of the techniques described in this book: for example problems depending upon the formation and solution of different equations; the task of making lists of possible alternatives and of answering questions about them; or the search for discrete optima. Written by the same authors as the highly successful Information Representation and Manipulation in a Computer, this book describes algorithms of mathematical methods and illustrates their application with examples. The mathematical background needed is elementary algebra and calculus. Numerous exercises are provided, with hints to their solutions.

Simulating a continuous process on a (computer) model provides a means of understanding how a system will behave when it is subject to particular constraints. Computers are of particular use for this purpose as the system is one which involves differential equations, eg. the behaviour of the vehicle suspension systems and chemical reactions. The book describes how analogue, digital and hybrid computers are used in simulating continuous systems. Their use is illustrated in the text by a number of simple problems and most chapters also contain examples of varying complexity selected from a range of scientific and engineering disciplines. A short appendix describes the functioning of analogue and hybrid units; for the rest of the book a knowledge of electric circuit theory is not required.