The Bluebit .NET Matrix Library provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems. Also provided are the associated matrix factorizations such as Eigen, LQ, LU, Cholesky, QR, SVD. Both real and complex matrices are supported.

eigenvectors, math, decomposition, eigenvalue, matrix, eigenvalues, cholesky, vector, eigenvector

The Bluebit .NET Matrix Library provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems. Also provided are the associated matrix factorizations such as Eigen, LQ, LU, Cholesky, QR, SVD. Both real and complex matrices are supported.

eigenvectors, math, decomposition, eigenvalue, matrix, eigenvalues, cholesky, vector, eigenvector

The Bluebit .NET Matrix Library provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems. Also provided are the associated matrix factorizations such as Eigen, LQ, LU, Cholesky, QR, SVD. Both real and complex matrices are supported.

eigenvectors, math, decomposition, eigenvalue, matrix, eigenvalues, cholesky, vector, eigenvector

The Bluebit .NET Matrix Library provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems. Also provided are the associated matrix factorizations such as Eigen, LQ, LU, Cholesky, QR, SVD. Both real and complex matrices are supported.

eigenvectors, math, decomposition, eigenvalue, matrix, eigenvalues, cholesky, vector, eigenvector

Modelling and simulation of continuous and time discrete automatic control systems in the time and frequency domain. Graphical, block oriented user interface with more than 80 basic blocks. Design and reusing of user-defined blocks. Presentation of simulation result as data series as well as time, Bode, Nichols-Black and Nyquists diagrams. Calculation of eigenvalues. Exporting to other applications for further processing. Creation of libraries.

control system, nyquist diagram, simulator, time domain, controller, eigenvalues, automation, black s plot, control, dynamics, bode diagram, frequency domain, closed loop

Performs computations associated with matrices, including solution of linear systems of equations (even over-determined or inconsistent systems and solution by LU factors), matrix operations (add, subtract, multiply), finds determinant, trace, inverse, adjoint, QR or LU factors, eigenvalues, eigenvectors, establish the definiteness of a symmetric matrix, scalar multiplication, transposition, shift, create general, identity, or symmetric matrices

equations, math, mathematics, linear algebra, science, matrix algebra, matrices, engineering