NMath User's Guide

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Contents

Part I - Introduction

Chapter 1. Overview

1.1 NMath Premium

1.2 Product Components

1.3 Software Requirements

1.4 NMath Assemblies

1.5 NMath License Key

1.6 NMath Configuration

1.7 Building and Deploying NMath Applications

1.8 Web Applications

1.9 Very Large Objects

1.10 Documentation

1.11 Visualization

1.12 Technical Support

Part II - The Core Namespace

Chapter 2. The Core Namespace

Chapter 3. Complex Number Types

3.1 Creating Complex Numbers

3.2 Value Operations on Complex Numbers

3.3 Logical Operations on Complex Numbers

3.4 Arithmetic Operations on Complex Numbers

3.5 Functions of Complex Numbers

Chapter 4. Viewing Data

4.1 DataBlock Classes

4.2 Slices and Ranges

Chapter 5. Vector Classes

5.1 Class Names

5.2 Creating Vectors

5.3 Value Operations on Vectors

5.4 Logical Operations on Vectors

5.5 Arithmetic Operations on Vectors

5.6 Functions of Vectors

5.7 Generic Functions

5.8 Vector Enumeration

Chapter 6. Matrix Classes

6.1 Class Names

6.2 Creating Matrices

6.3 Value Operations on Matrices

6.4 Logical Operations on Matrices

6.5 Arithmetic Operations on Matrices

6.6 Vector Views

6.7 Functions of Matrices

6.8 Generic Functions

6.9 Matrix Enumeration

Chapter 7. Solutions of Linear Systems

7.1 Class Names

7.2 Creating LU Factorizations

7.3 Using LU Factorizations

7.4 Static Methods

Chapter 8. Least Squares

8.1 Class Names

8.2 Creating Least Squares Solutions

8.3 Using Least Squares Solutions

8.4 Nonnegative Least Squares Solutions

Chapter 9. Random Number Generators

9.1 Scalar Random Number Generators

9.2 Vectorized Random Number Generators

Chapter 10. Fourier Transforms, Convolution and Correlation

10.1 Fast Fourier Transforms

10.2 Convolution and Correlation

Chapter 11. Histograms

11.1 Creating Histograms

11.2 Adding Data to Histograms

11.3 Value Operations of Histograms

11.4 Displaying Histograms

Chapter 12. Calculus

12.1 Encapsulating Functions

12.2 Numerical Integration

12.3 Differentiation

12.4 Polynomials

12.5 Function Interpolation

Chapter 13. Signal Processing

13.1 Moving Window Filtering

13.2 Savitzky-Golay Filtering

13.3 Peak Finding

Part III - The Matrix Namespace

Chapter 14. The Matrix Namespace

Chapter 15. Structured Sparse Matrix Types

15.1 Lower Triangular Matrices

15.2 Upper Triangular Matrices

15.3 Symmetric Matrices

15.4 Hermitian Matrices

15.5 Banded Matrices

15.6 Tridiagonal Matrices

15.7 Symmetric Banded Matrices

15.8 Hermitian Banded Matrices

Chapter 16. Using The Structured Sparse Matrix Classes

16.1 Creating Matrices

16.2 Value Operations on Matrices

16.3 Logical Operations on Matrices

16.4 Arithmetic Operations on Matrices

16.5 Vector Views

16.6 Functions of Matrices

16.7 Generic Functions

Chapter 17. General Sparse Vectors and Matrices

17.1 Sparse Vectors

17.2 Sparse Matrices

17.3 Sparse Matrix Factorizations

Chapter 18. Structured Sparse Matrix Factorizations

18.1 Factorization Classes

18.2 Creating Factorizations

18.3 Using Factorizations

Chapter 19. Decompositions

19.1 QR Decompositions

19.2 Singular Value Decompositions

Chapter 20. Least Squares Solutions

20.1 Ordinary Least Squares Methods

20.2 Creating Ordinary Least Squares Objects

20.3 Using Ordinary Least Squares Objects

20.4 Weighted Least Squares

20.5 Iteratively Reweighted Least Squares

Chapter 21. EigenValue Problems

21.1 Eigenvalue Classnames

21.2 Using the Eigenvalue Classes

21.3 Using the Eigenvalue Server Classes

Part IV - The Analysis Namespace

Chapter 22. The Analysis Namespace

Chapter 23. Encapsulating Multivariate Functions

23.1 Creating Multivariate Functions

23.2 Evaluating Multivariate Functions

23.3 Algebraic Manipulation of Multivariate Functions

Chapter 24. Minimizing Univariate Functions

24.1 Bracketing a Minimum

24.2 Minimizing Functions Without Calculating the Derivative

24.3 Minimizing Derivable Functions

Chapter 25. Minimizing Multivariate Functions

25.1 Minimizing Functions Without Calculating the Derivative

25.2 Minimizing Derivable Functions

Chapter 26. Simulated Annealing

26.1 Temperature

26.2 Annealing Schedules

26.3 Minimizing Functions by Simulated Annealing

26.4 Annealing History

Chapter 27. Linear Programming

27.1 Encapsulating LP Problems

27.2 Solving LP Problems

Chapter 28. Nonlinear and Quadratic Programming

28.1 Objective and Constraint Function Classes

28.2 Nonlinear Programming

28.3 Quadratic Programming

28.4 Constrained Least Squares

Chapter 29. Fitting Polynomials

29.1 Creating PolynomialLeastSquares

29.2 Properties of PolynomialLeastSquares

Chapter 30. Nonlinear Least Squares

30.1 Nonlinear Least Squares Interfaces

30.2 Trust-Region Minimization

30.3 Levenberg-Marquardt Minimization

30.4 Nonlinear Least Squares Curve Fitting

30.5 Nonlinear Least Squares Surface Fitting

Chapter 31. Finding Roots of Univariate Functions

31.1 Finding Function Roots Without Calculating the Derivative

31.2 Finding Function Roots of Derivable Functions

Chapter 32. Integrating Multivariable Functions

32.1 Creating TwoVariableIntegrators

32.2 Integrating Functions of Two Variables

Chapter 33. Differential Equations

33.1 Encapsulating Differential Equations

33.2 Solving Differential Equations

33.3 Dormand–Prince Method

Part V - Miscellaneous Topics

Chapter 30. Serialization

30.1 Binary Serialization

30.2 SOAP Serialization

30.3 XML Serialization

Chapter 31. Database Integration

31.1 Creating ADO.NET Objects from Vectors and Matrices

31.2 Creating Vector and Matrices from ADO.NET Objects

Chapter 32. Error Handling

32.1 Exception Types

Chapter 33. NMath Premium

33.1 Supported Features

33.2 NMath Premium Assemblies

33.3 NMath Premium Licensing

33.4 Bridge Management

33.5 GPU Logging

33.6 Bridge Tuning

33.7 Reusing Bridges

33.8 Bridge Visualization

33.9 Overriding Bridge Routing

Index


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