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Numerical Methods, Algorithms and Tools in C#

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ISBN-10: 0849374790

ISBN-13: 9780849374791

Edition: 2009

Authors: Waldemar Dos Passos

List price: $150.00
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Putting electrical engineers and mathematicians, as well as programmers, ahead of the curve, and making sure they can apply that advantage, this volume provides a broad collection of computational tools for the easy-to-learn and relatively new programming language of C#.
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Book details

List price: $150.00
Copyright year: 2009
Publisher: CRC Press LLC
Publication date: 10/23/2009
Binding: Hardcover
Pages: 598
Size: 6.50" wide x 9.25" long x 1.50" tall
Weight: 2.134
Language: English

Waldemar Dos Passos is a computer programming consultant in the Silicon Valley area of California. After completing his undergraduate education at the University of California, Berkeley, Dr. Dos Passos earned an M.S. in computer science and engineering along with a Ph.D. in physics from the University of Michigan, Ann Arbor. With more than twenty years of computer programming experience, he has published several papers in physics journals.

Introduction
C# and the.NET Framework
Installing C# and the.NET Framework
Overview of Object-Oriented Programming (OOP)
Your First C# Program
Overview of the IDE Debugger
Overview of the C# Language
Data Types
Value Types
Reference Types
Type-Parameter Types
Pointer Types
Variable Declaration
Constant Declaration
Nullable Types
Scope
Characters
Strings
Formatting of Output Data
Type Conversion
Reading Keyboard Input Data
Basic Expressions and Operators
Program Flow Mechanisms
Jump Statements
Arrays
Enumerations
Structures
Exceptions
Classes
Constructors and Destructors
Properties
Methods
Indexers
Overloading Methods, Constructors and Operators
Delegates
Events
Collections
File Input/Output
Output Reliability, Accuracy and Precision
The.NET Framework Math Class Library
Introduction
The.NET Framework Math Class - Fields
The Math. pi and Math. e Fields
The.NET Framework Math Class - Methods
The Minimum and Maximum Methods
The Power, Exponential and Logarithmic Methods
Special Multiplication, Division and Remainder Methods
The Absolute Value Method
The Sign Method
Angular Units of Measurement
The Trigonometric Functions
The Inverse Trigonometric Functions
The Hyperbolic Functions
The Inverse Hyperbolic Functions
Rounding Off Numeric Data
The Ceiling Method
The Floor Method
The Truncation Method
The Round Method
Vectors and Matrices
Introduction
A Real Number Vector Library in C#
A Real Number Matrix Library in C#
Complex Numbers
Introduction
Fundamental Concepts
Complex Number Arithmetic
Elementary Functions of a Complex Number
Exponentials
Logarithms
Powers and Roots
Trigonometric and Hyperbolic Functions
Inverse Trigonometric and Hyperbolic Functions
A Complex Number Library in C#
A Complex Number Vector Library in C#
A Complex Number Matrix Library in C#
Generic vs. Non-Generic Coding
Sorting and Searching Algorithms
Introduction
Sorting Algorithms
Comparison Sorts
Bubble Sort
Cocktail Sort
Odd-Even Sort
Comb Sort
Gnome Sort
Quicksort
Insertion Sort
Shell Sort
Selection Sort
Merge Sort
Bucket Sort
Heap Sort
Count Sort
Radix Sort
Search Algorithms
Linear Search
Binary Search
Interpolation Search
Searching for the Maximum and Minimum Values
Searching for the N-th Largest or M-th Smallest Value
Some Useful Utilities
Bits and Bytes
Introduction
Numeric Systems
Bit Manipulation and Bitwise Operators
Assorted Bits and Bytes
Interpolation
Introduction
Linear Interpolation
Bilinear Interpolation
Polynomial Interpolation
Lagrange Interpolation
Barycentric Interpolation
Newton's Divided Differences Interpolation
Cubic Spline Interpolation
Natural Cubic Splines
Clamped Cubic Splines
Linear Equations
Introduction
Gaussian Elimination
Gauss-Jordan Elimination
LU Decomposition
Iteration Methods
Gauss-Jacobi Iteration
Gauss-Seidel Iteration
Eigenvalues and Jacobi's Algorithm
Nonlinear Equations
Introduction
Linear Incremental Method
Bisection Method
The Secant Method
False Positioning Method
Fixed Point Iteration
Newton-Raphson Method
Random Numbers
Introduction
The C# Built-In Random Number Generator
Other Random Number Generators
True Random Number Generators
Random Variate Generation Methods
Histograms
Random Variate Generation
Discrete Distributions
Bernoulli Distribution
Binoulli Distribution
Geometric Distribution
Negative Binomial Distribution
Poisson Distribution
Uniform Distribution (discrete)
Continuous Distributions
Beta Distribution
Beta Prime Distribution
Cauchy Distribution
Chi Distribution
Chi-Square Distribution
Erlang Distribution
Exponential Distribution
Extreme Value Distribution
Gamma Distribution
Laplace Distribution
Logistic Distribution
Lognormal Distribution
Normal Distribution
Pareto Distribution
Rayleigh Distribution
Student-t Distribution
Triangular Distribution
Uniform Distribution (continuous)
Weibull Distribution
Shuffling Algorithms
Adding Random Noise to Data
Removing Random Noise from Data
Numerical Differentiation
Introduction
Finite Difference Formulas
Forward Difference Method
Backward Difference Method
Central Difference Method
Improved Central Difference Method
Richardson Extrapolation
Derivatives by Polynomial Interpolation
Numerical Integration
Introduction
Newton-Cotes Formulas
Rectangle Method
Midpoint Method
Trapezoidal Method
Simpson's Method
Simpson's 1/3 Method
Simpson's 3/8 Method
Romberg Integration
Gaussian Quadrature Methods
Gauss-Legendre Integration
Gauss-Hermite Integration
Gauss-Leguerre Integration
Gauss-Chebyshev Integration
Multiple Integration
Monte Carlo Methods
Monte Carlo Integration
The Metropolis Algorithm
Convolution Integrals
Statistical Functions
Introduction
Some Useful Tools
Basic Statistical Functions
Mean and Weighted Mean
Geometric and Weighted Geometric Mean
Harmonic and Weighted Harmonic Mean
Truncated Mean
Root Mean Square
Median, Range and Mode
Mean Deviation
Mean Deviation of the Mean
Mean Deviation of the Median
Variance and Standard Deviation
Moments About the Mean
Skewness
Kurtosis
Covariance and Correlation
Miscellaneous Utilities
Percentiles and Rank
Special Functions
Introduction
Factorials
Combinations and Permutations
Combinations
Permutations
Gamma Function
Beta Function
Error Function
Sine and Cosine Integral Functions
Laguerre Polynomials
Hermite Polynomials
Chebyshev Polynomials
Legendre Polynomials
Bessel Functions
Curve Fitting Methods
Introduction
Least Squares Fit
Straight-Line Fit
Weighted Least Squares Fit
Weighted Straight-Line Fit
Linear Regression
Polynomial Fit
Exponential Fit
The X(2) Test for Goodness of Fit
Ordinary Differential Equations
Introduction
Euler Method
Runge-Kutta Methods
Second-Order Runge-Kutta Method
Fourth-Order Runge-Kutta Method
Runge-Kutta-Fehlberg Method
Coupled Differential Equations
Partial Differential Equations
Introduction
The Finite Difference Method
Parabolic Partial Differential Equations
The Crank-Nicolson Method
Hyperbolic Partial Differential Equations
Elliptic Partial Differential Equations
Optimization Methods
Introduction
Gradient Descent Method
Linear Programming
The Revised Simplex Method
Simulated Annealing Method
Genetic Algorithms
References
Index