The ESPRIT Algorithm and Central Limit Error Scaling

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Abstract and 1 Introduction

1.1 EsPrit Algorithm and Middle Error Limit

1.2 Contribution

1.3 related work

1

2 proof of the central limit of error in scale

3 proof of the optimal error scale

4 theories of second-order eigenvector perturbation theory

5 strong comparisons of eigenvector

5.1 construction of “good” p

5.2 Expanding Taylor with respect to error terms

5.3 Taylor's Error Cancel

5.4 proof of theorem 5.1

A preliminaries

B Vandermonde Matrice

C Delayed proofs for Section 2

D Deponted proofs for Section 4

E Deponted proofs for Section 5

F lower bonded for spectral estimate

References

1.1 EsPrit Algorithm and Middle Error Limit

Determine locations and intensity vectors

The minimum is taken with all permutations π to {1 ,. . . , r}.