Extreme Optimization™: Complexity made simple.

Math and Statistics
Libraries for .NET

  • Home
  • Features
    • Math Library
    • Vector and Matrix Library
    • Statistics Library
    • Performance
    • Usability
  • Documentation
    • Introduction
    • Math Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Reference
  • Resources
    • Downloads
    • QuickStart Samples
    • Sample Applications
    • Frequently Asked Questions
    • Technical Support
  • Blog
  • Order
  • Company
    • About us
    • Testimonials
    • Customers
    • Press Releases
    • Careers
    • Partners
    • Contact us
Introduction
Deployment Guide
Nuget packages
Configuration
Using Parallelism
Expand Mathematics Library User's GuideMathematics Library User's Guide
Expand Vector and Matrix Library User's GuideVector and Matrix Library User's Guide
Expand Data Analysis Library User's GuideData Analysis Library User's Guide
Expand Statistics Library User's GuideStatistics Library User's Guide
Expand Data Access Library User's GuideData Access Library User's Guide
Expand ReferenceReference
  • Extreme Optimization
    • Features
    • Solutions
    • Documentation
    • QuickStart Samples
    • Sample Applications
    • Downloads
    • Technical Support
    • Download trial
    • How to buy
    • Blog
    • Company
    • Resources
  • Documentation
    • Introduction
    • Deployment Guide
    • Nuget packages
    • Configuration
    • Using Parallelism
    • Mathematics Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Data Access Library User's Guide
    • Reference
  • Vector and Matrix Library User's Guide
    • Basic Concepts
    • Vectors
    • Matrices
    • Structured Matrix Types
    • Matrix Decompositions
    • Sparse Vectors and Matrices
    • Complex Linear Algebra
    • Single-Precision Linear Algebra
    • Distributed and GPU Computing
  • Structured Matrix Types
    • Triangular Matrices
    • Symmetrical Matrices
    • Hermitian Matrices
    • Band Matrices
    • Diagonal Matrices

Structured Matrix Types

Extreme Optimization Numerical Libraries for .NET Professional

Matrices come in many shapes and sizes. When the matrix exhibits a definite structure, calculations can often be sped up significantly. Storage requirements may also be significantly reduced. It is therefore useful to define different matrix types to take advantage of these improvements.

The Extreme Optimization Numerical Libraries for .NET includes classes for upper- and lower-triangular, symmetrical, and Hermitian matrices. These classes are contained in the Extreme.Mathematics.LinearAlgebra namespace.

All matrix code uses optimized implementations of the Basic Linear Algebra Subroutines (BLAS) and the Linear Algebra PACKage (LAPACK) wherever possible.

In this section:

  • Triangular Matrices
  • Symmetrical Matrices
  • Band Matrices
  • Diagonal Matrices

Copyright (c) 2004-2021 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

Copyright © 2004-2021, Extreme Optimization. All rights reserved.
Extreme Optimization, Complexity made simple, M#, and M Sharp are trademarks of ExoAnalytics Inc.
Microsoft, Visual C#, Visual Basic, Visual Studio, Visual Studio.NET, and the Optimized for Visual Studio logo
are registered trademarks of Microsoft Corporation.