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[PDF] Top 20 If a matrix has only a single eigenvalue how sensitive Is this eigenvalue

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If a matrix has only a single eigenvalue how sensitive Is this eigenvalue

If a matrix has only a single eigenvalue how sensitive Is this eigenvalue

... Our numerical experiments have indicated that Corollary 3.2 can be very pes- simistic. That's because it uses only a small part of the perturbed eigenvector, namely the part in the unperturbed left eigenspace ... See full document

11

If a matrix has only a single eigenvalue how sensitive Is this eigenvalue? II

If a matrix has only a single eigenvalue how sensitive Is this eigenvalue? II

... [r] ... See full document

12

A New Approach for Isomorphism Identification among Compound Kinematic Chains and Mechanisms

A New Approach for Isomorphism Identification among Compound Kinematic Chains and Mechanisms

... adjacency matrix is proposed. The proposed method not only effective but also more efficient than that are based on the adjacency matrices and capable of detecting isomorphism in all types of compound KC, ... See full document

6

Eigenvectors of block circulant and alternating circulant matrices

Eigenvectors of block circulant and alternating circulant matrices

... For vectors of the form (12) the set (16) of n eigenvector equations of order κ, for the n values of ρ, is equivalent to the single eigenvector equation (13), of order nκ. For each of the n values of ρ, the ... See full document

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Inverse eigenvalue problem for matrices whose graph is a banana tree

Inverse eigenvalue problem for matrices whose graph is a banana tree

... vertices, we denote by S(G) the set of all real symmetric matrices whose graph is G. A matrix whose graph is a tree is called an acyclic matrix. Some simple examples of acyclic matrices are the matrices ... See full document

13

An Automated Model for Fitting a Hemi Ellipsoid and Calculating Eigenvalues Using Matrices

An Automated Model for Fitting a Hemi Ellipsoid and Calculating Eigenvalues Using Matrices

... When automating, a trade-off has to be made between accuracy and computation time. Depending on the ne- cessity for precision, a decreased stepping parameter may be desired to ensure the best possible fit occurs. ... See full document

7

New upper bounds for \(\|A^{ 1}\| {\infty}\) of strictly diagonally dominant M matrices

New upper bounds for \(\|A^{ 1}\| {\infty}\) of strictly diagonally dominant M matrices

... inverse matrix of a strictly diagonally dominant M-matrix is given, and the lower bound for the minimum eigenvalue of the matrix is ...inverse matrix of a strictly α -diagonally ... See full document

8

A New DOA Estimation Method Based on Spatial Structure of Array Signals

A New DOA Estimation Method Based on Spatial Structure of Array Signals

... Where, P  E { S ( t ) S ( t ) H } . If L  M , then all the elements of  are zero. Otherwise, except the element ( 1 , L ) , ( 2 , L  1 ) , ( M  L  1 , M ) are  2 , the elements remaining are zero. We will change ... See full document

5

Optimal Bounds for the Largest Eigenvalue of a 3 × 3 Correlation Matrix

Optimal Bounds for the Largest Eigenvalue of a 3 × 3 Correlation Matrix

... More recently, Zhan [5] obtains the optimal bounds for the smallest and largest eigenvalues of real symmetric matrices whose entries belong to a fixed finite interval.. However, when res[r] ... See full document

8

Bargmann and Neumann System of the Second- Order Matrix Eigenvalue Problem

Bargmann and Neumann System of the Second- Order Matrix Eigenvalue Problem

... The results of this paper have been algebraic in nature. We have considered the second order matrix eigenvalue problem (1). In the first part of section 2, we gave Lax representation and evolution equation ... See full document

8

Left Eigenvector of a Stochastic Matrix

Left Eigenvector of a Stochastic Matrix

... In the noncommutative case, we must involve inverses of elements of the skew field and as these may be undefined, we take a generic noncommutative stochastic matrix: this is the matrix of noncommuting vari- ... See full document

13

A comparison of iterative and DFT-based polynomial matrix eigenvalue decompositions

A comparison of iterative and DFT-based polynomial matrix eigenvalue decompositions

... As both iterative and DFT-based PEVD algorithms reach a solution to (1) through different methodologies, a comparison of their decomposition performance is of interest. Here, we compare the decompositions of SMD — as a ... See full document

5

Some inequalities for the minimum eigenvalue of the Hadamard product of an M matrix and an inverse M matrix

Some inequalities for the minimum eigenvalue of the Hadamard product of an M matrix and an inverse M matrix

... It is easy to see that A is a nonsingular M-matrix and A – is doubly stochastic. The results obtained from Theorem  for n = ,  and T =  are listed in Table , where T is defined in Example . In fact, τ (A ... See full document

9

Nonlinear eigenvalue problems

Nonlinear eigenvalue problems

... linear eigenvalue problems this limit is accessible by using WKB ...nonlinear eigenvalue problem solved in this paper the large-eigenvalue limit is accessible because the problem becomes linear in ... See full document

16

Smooth eigenvalue correction

Smooth eigenvalue correction

... of eigenvalue distribution Both (LSA) and (GSA) apply limit analysis to find a rela- tion between the population eigenvalue set and the sample eigenvalue ...the eigenvalue distribution for the ... See full document

16

Nonlinear eigenvalue problems

Nonlinear eigenvalue problems

... This remarkable and deceptively simple looking differential equation was given as an exercise in the text by Bender and Orszag [1]. Since then, it and closely related differential equations have arisen in a number of ... See full document

16

Systematic Link of Modal Identification with Model Updating

Systematic Link of Modal Identification with Model Updating

... The elastic modulus of the model can be obtained by model updating using the eigenvalue and strain measurement mode shape provided by the modal identification. Figure 6(a) compares the elastic moduli of the ... See full document

13

Evaluation of drought resistance in Iris germanica L. based on subordination function and principal component analysis

Evaluation of drought resistance in Iris germanica L. based on subordination function and principal component analysis

... It has large flowers in rich and bright colors and is widely used in ...germanica has been one of the important factors to be considered in the allocation of plants for urban ... See full document

9

Some inequalities for the minimum eigenvalue of the Hadamard product of an M matrix and its inverse

Some inequalities for the minimum eigenvalue of the Hadamard product of an M matrix and its inverse

... AMS Subject Classification: 15A18; 15A42 Keywords: Hadamard product; M-matrix; inverse M-matrix; strictly diagonally dominant matrix; eigenvalue.. This is an Open Access article distribut[r] ... See full document

9

A modified Leverrier-Faddeev algorithm for matrices with multiple-eigenvalues

A modified Leverrier-Faddeev algorithm for matrices with multiple-eigenvalues

... The Ieverrier algorithm as modified by Faddeev gives the characteristic equation of a matrix A, its inverse, and the eigenvector corresponding to a simple eigenvalue h [r] ... See full document

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