### Some articles on *eigenvalue, eigenvalues*:

Preconditioner - Preconditioning For

...

**Eigenvalue**Problems...

**Eigenvalue**problems can be framed in several alternative ways, each leading to its own preconditioning ... Knowing (approximately) the targeted**eigenvalue**, one can compute the corresponding eigenvector by solving the related homogeneous linear system, thus allowing to use preconditioning for linear system ... Finally, formulating the**eigenvalue**problem as optimization of the Rayleigh quotient brings preconditioned optimization techniques to the scene ...Segmentation-based Object Categorization - Segmentation Using Normalized Cuts - The Ncut Algorithm

... can be solved by solving the generalized

... can be solved by solving the generalized

**eigenvalue**problem for the second smallest generalized**eigenvalue**... Solve for eigenvectors with the smallest**eigenvalues**... Use the eigenvector with the smallest**eigenvalue**to bipartition the graph (e.g ...Matrix Differential Equation - Solved Example of A Matrix ODE - Second Step

... For each of the

... For each of the

**eigenvalues**calculated we are going to have an individual eigenvector ... For our first**eigenvalue**, which is, we have the following Simplifying the above expression by applying basic matrix multiplication rules we have ... required eigenvector for this particular**eigenvalue**...Mathematical Description - Spatial Correlation Matrices

... Under the Kronecker model, the spatial correlation depends directly on the

... Under the Kronecker model, the spatial correlation depends directly on the

**eigenvalue**distributions of the correlation matrices and ... spatial direction of the channel and its corresponding**eigenvalue**describes the average channel/signal gain in this direction ... spatial correlation is represented by large**eigenvalue**spread in or, meaning that some spatial directions are statistically stronger than others ...Power Iteration - Analysis

... of corresponding to the dominant

... of corresponding to the dominant

**eigenvalue**... Since the dominant**eigenvalue**of is unique, the first Jordan block of is the matrix, where is the largest**eigenvalue**of A in magnitude ... By assumption, has a nonzero component in the direction of the dominant**eigenvalue**, so ...Related Subjects

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