C Programming and Numerical Analysis

C Programming and Numerical Analysis
Author: Seiichi Nomura
Publisher: Springer Nature
Total Pages: 184
Release: 2022-05-31
Genre: Technology & Engineering
ISBN: 3031796055
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This book is aimed at those in engineering/scientific fields who have never learned programming before but are eager to master the C language quickly so as to immediately apply it to problem solving in numerical analysis. The book skips unnecessary formality but explains all the important aspects of C essential for numerical analysis. Topics covered in numerical analysis include single and simultaneous equations, differential equations, numerical integration, and simulations by random numbers. In the Appendices, quick tutorials for gnuplot, Octave/MATLAB, and FORTRAN for C users are provided.

MATLAB Programming for Numerical Analysis

MATLAB Programming for Numerical Analysis
Author: Cesar Lopez
Publisher: Apress
Total Pages: 238
Release: 2014-09-22
Genre: Computers
ISBN: 1484202953
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MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. Programming MATLAB for Numerical Analysis introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. You will first become familiar with the MATLAB environment, and then you will begin to harness the power of MATLAB. You will learn the MATLAB language, starting with an introduction to variables, and how to manipulate numbers, vectors, matrices, arrays and character strings. You will learn about MATLAB’s high-precision capabilities, and how you can use MATLAB to solve problems, making use of arithmetic, relational and logical operators in combination with the common functions and operations of real and complex analysis and linear algebra. You will learn to implement various numerical methods for optimization, interpolation and solving non-linear equations. You will discover how MATLAB can solve problems in differential and integral calculus, both numerically and symbolically, including techniques for solving ordinary and partial differential equations, and how to graph the solutions in brilliant high resolution. You will then expand your knowledge of the MATLAB language by learning how to use commands which enable you to investigate the convergence of sequences and series, and explore continuity and other analytical features of functions in one and several variables.

Numerical C

Numerical C
Author: Philip Joyce
Publisher: Apress
Total Pages: 319
Release: 2019-09-20
Genre: Computers
ISBN: 1484250648
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Learn applied numerical computing using the C programming language, starting with a quick primer on the C programming language and its SDK. This book then dives into progressively more complex applied math formula for computational methods using C with examples throughout and a larger, more complete application towards the end. Numerical C starts with the quadratic formula for finding solutions to algebraic equations that model things such as price vs. demand or rise vs. run or slip and more. Later in the book, you'll work on the augmented matrix method for simultaneous equations. You’ll also cover Monte Carlo method model objects that could arise naturally as part of the modeling of a real-life system, such as a complex road network, the transport of neutrons, or the evolution of the stock market. Furthermore, the Monte Carlo method of integration examines the area under a curve including rendering or ray tracing and the shading in a region. Furthermore, you'll work with the product moment correlation coefficient: correlation is a technique for investigating the relationship between two quantitative, continuous variables, for example, age and blood pressure. By the end of the book, you'll have a feeling for what computer software could do to help you in your work and apply some of the methods learned directly to your work. What You Will Learn Gain software and C programming basicsWrite software to solve applied, computational mathematics problems Create programs to solve equations and calculus problems Use the trapezium method, Monte Carlo method, line of best fit, product moment correlation coefficient, Simpson’s rule, and matrix solutions Write code to solve differential equations Apply one or more of the methods to an application case study Who This Book Is For Those with an existing knowledge of rudimentary mathematics (school level) and some basic programming experience. This is also important to people who may work in mathematics or other areas (for example, life sciences, engineering, or economics) and need to learn C programming.

NUMERICAL ANALYSIS

NUMERICAL ANALYSIS
Author: Vinay Vachharajani
Publisher: BPB Publications
Total Pages: 594
Release: 2018-06-01
Genre: Computers
ISBN: 9387284611
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Description:This book is Designed to serve as a text book for the undergraduate as well as post graduate students of Mathematics, Engineering, Computer Science.COVERAGE:Concept of numbers and their accuracy, binary and decimal number system, limitations of floating point representation.Concept of error and their types, propagation of errors through process graph.Iterative methods for finding the roots of algebraic and transcendental equations with their convergence, methods to solve the set of non-linear equations, methods to obtain complex roots.Concept of matrices, the direct and iterative methods to solve a system of linear algebraic equations.Finite differences, interpolation and extrapolation methods, cubic spline, concept of curve fitting.Differentiation and integration methods.Solution of ordinary and partial differential equations SALIENT FEATURES:Chapters include objectives, learning outcomes, multiple choice questions, exercises for practice and solutions.Programs are written in C Language for Numerical methods.Topics are explained with suitable examples.Arrangement (Logical order), clarity, detailed presentation and explanation of each topic with numerous solved and unsolved examples.Concise but lucid and student friendly presentation for derivation of formulas used in various numerical methods. Table Of Contents:Computer ArithmeticError Analysis Solution of Algebraic and Transcendental Equations Solution of System of Linear Equations and Eigen value Problems Finite Differences Interpolation Curve Fitting and Approximation Numerical Differentiation Numerical Integration Difference Equations Numerical Solution of Ordinary Differential Equations Numerical Solution of Partial Differential Equations Appendix - I Case Studies / Applications Appendix - II Synthetic Division Bibliography Index

Computer Programming and Numerical Analysis Revised Edition with C: A Integrated Approach

Computer Programming and Numerical Analysis Revised Edition with C: A Integrated Approach
Author: N. Datta
Publisher: Universities Press
Total Pages: 520
Release: 2003-10
Genre: C (Computer program language)
ISBN: 9788173714511
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The availability of high-speed digital computers has led to the widespread study of computer programming and numerical analysis in Indian universities and technological institutes. This book presents the theory and applications of numerical methods for the solution of various types of computational problems in science and engineering.

Numerical Methods in "C"

Numerical Methods in
Author: J.G. Kori
Publisher: Firewall Media
Total Pages: 172
Release: 2006
Genre: C (Computer program language)
ISBN: 9788170082101
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PETSc for Partial Differential Equations: Numerical Solutions in C and Python

PETSc for Partial Differential Equations: Numerical Solutions in C and Python
Author: Ed Bueler
Publisher: SIAM
Total Pages: 407
Release: 2020-10-22
Genre: Mathematics
ISBN: 1611976316
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The Portable, Extensible Toolkit for Scientific Computation (PETSc) is an open-source library of advanced data structures and methods for solving linear and nonlinear equations and for managing discretizations. This book uses these modern numerical tools to demonstrate how to solve nonlinear partial differential equations (PDEs) in parallel. It starts from key mathematical concepts, such as Krylov space methods, preconditioning, multigrid, and Newton’s method. In PETSc these components are composed at run time into fast solvers. Discretizations are introduced from the beginning, with an emphasis on finite difference and finite element methodologies. The example C programs of the first 12 chapters, listed on the inside front cover, solve (mostly) elliptic and parabolic PDE problems. Discretization leads to large, sparse, and generally nonlinear systems of algebraic equations. For such problems, mathematical solver concepts are explained and illustrated through the examples, with sufficient context to speed further development. PETSc for Partial Differential Equations addresses both discretizations and fast solvers for PDEs, emphasizing practice more than theory. Well-structured examples lead to run-time choices that result in high solver performance and parallel scalability. The last two chapters build on the reader’s understanding of fast solver concepts when applying the Firedrake Python finite element solver library. This textbook, the first to cover PETSc programming for nonlinear PDEs, provides an on-ramp for graduate students and researchers to a major area of high-performance computing for science and engineering. It is suitable as a supplement for courses in scientific computing or numerical methods for differential equations.