Synopses & Reviews
Erwin Kreyszig’s
Advanced Engineering Mathematics, 9th Editionintroduces engineers and computer scientists to advanced math topics as they relate to practical problems.
In today’s world of increasingly complex engineering problems, powerful new mathematical and computational methods, and enormous computer capacities, you can get overwhelmed by little things you will only occasionally use. Instead, you need to learn how to think mathematically and gain a firm grasp of the interrelationship among theory, computing, and experiment. That’s why Kreyszig’s text helps you develop a solid understanding of the basic principles and methods of advanced engineering mathematics in all three phases of problem solving: Modeling, Solving, and Interpreting. This best-selling text is known for its comprehensive coverage, careful and correct mathematics, outstanding exercises, and self-contained chapters.
Key Features
- New problem sets.
- New Computer Experiments, using the computer as an instrument of “experimental mathematics” for exploration and research.
- More on modeling and selection methods.
- Accurate and solid theoretical foundation.
- Clear examples and exposition of material.
- Modern and standard notations.
Synopsis
Introduces engineers, computer scientists, and physicists to advanced math topics as they relate to practical problems. The material is arranged into seven independent parts: ODE; Linear Algebra, Vector calculus; Fourier Analysis and Partial Differential Equations; Complex Analysis; Numerical methods; Optimization, graphs; Probability and Statistics.
Synopsis
A revision of the market leader, Kreyszig is known for its comprehensive coverage, careful and correct mathematics, outstanding exercises, helpful worked examples, and self-contained subject-matter parts for maximum teaching flexibility. The new edition provides invitations - not requirements - to use technology, as well as new conceptual problems, and new projects that focus on writing and working in teams.
Table of Contents
ORDINARY DIFFERENTIAL EQUATIONS.
First-Order Differential Equations.
Linear Differential Equations of Second and Higher Order.
Systems of Differential Equations, Phase Plane, Qualitative Methods.
Series Solutions of Differential Equations. Special Functions.
Laplace Transforms.
LINEAR ALGEBRA, VECTOR CALCULUS.
Linear Algebra: Matrices, Vectors, Determinants. Linear Systems of Equations.
Linear Algebra: Matrix Eigenvalue Problems.
Vector Differential Calculus. Grad, Div, Curl.
Vector Integral Calculus. Integral Theorems.
FOURIER ANALYSIS AND PARTIAL DIFFERENTIAL EQUATIONS.
Fourier Series, Integrals, and Transforms.
Partial Differential Equations.
COMPLEX ANALYSIS.
Complex Numbers and Functions. Conformal Mapping.
Complex Integration.
Power Series, Taylor Series.
Laurent Series, Residue Integration.
Complex Analysis Applied to Potential Theory.
NUMERICAL METHODS.
Numerical Methods in General.
Numerical Methods in Linear Algebra.
Numerical Methods for Differential Equations.
OPTIMIZATION, GRAPHS.
Unconstrained Optimization, Linear Programming.
Graphs and Combinatorial Optimization.
PROBABILITY AND STATISTICS.
Data Analysis. Probability Theory.
Mathematical Statistics.
Appendices.
Index.