Solutions Manual for Fundamentals of Computer Numerical Analysis

Engineering & Transportation

Kandel, Abraham

Friedman, Menahem

Engineering

Fundamentals of Computer Numerical Analysis presents a comprehensive, logical approach to learning pragmatic numerical analysis. The book begins with an introduction to complex numbers and calculus and builds iii a modular fashion to a culmination with ordinary and partial differential equations. Each chapter is self-contained and requires only the knowledge of the previous chapters in order to be fully understood.

Fundamentals of Computer Numerical Analysis

Computers & Technology

Programming

CRC-Press

Another Calculus book? As long as students find calculus scary, the failure rate in mathematics is higher than in all other subjects, and as long as most people mistakenly believe that only geniuses can learn and understand mathematics, there will always be room for a new book of Calculus. We call it Calculus Light.This book is designed for a one semester course in "light" calculus – mostly single variable, meant to be used by undergraduate students without a wide mathematical background and who do not major in mathematics but study subjects such as engineering, biology or management information systems. The first chapter contains a historical background of calculus. Every scientific achievement involves people and therefore characterized by victories and disappointments, intrigues and hope. All of these elements exist in the story behind calculus and when you add the time dimension, starting 2400 years ago, it is a saga. We hope the reader enjoys reading this chapter as much as we enjoyed the writing.In addition to classic calculus the book provides tools for practical applications such as Fourier series, Lagrange multipliers and elementary numerical methods.

Calculus Light (Intelligent Systems Reference Library, 9)

Computer Science

Springer

<p>This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.</p>

Introduction to Pattern Recognition : Statistical, Structural, Neural and Fuzzy Logic Approaches (Series in Machine Perception and Artificial Intelligence)

World Scientific Publishing Company

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