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Exact confidence interval for magnitude-squared coherence estimates

Exact confidence interval for magnitude-squared coherence estimates
Exact confidence interval for magnitude-squared coherence estimates
The magnitude-squared coherence function is widely used in many applications. The approximate confidence interval is only reliable for large data segments. In this letter, an iterative algorithm is provided to compute the exact confidence interval from the cumulative distribution function. In order to use the confidence interval conveniently in practice, some libraries are provided, using the iterative algorithm and cubic spline interpolation.
326-329
Wang, Shou Yan
cea544a8-8562-43cb-9330-19f13c22c1d2
Tang, Meng Xing
a09d61ae-8219-46c4-83cd-1bf3fab0b6ab
Wang, Shou Yan
cea544a8-8562-43cb-9330-19f13c22c1d2
Tang, Meng Xing
a09d61ae-8219-46c4-83cd-1bf3fab0b6ab

Wang, Shou Yan and Tang, Meng Xing (2004) Exact confidence interval for magnitude-squared coherence estimates. IEEE Signal Processing Letters, 11 (3), 326-329. (doi:10.1109/LSP.2003.822897).

Record type: Article

Abstract

The magnitude-squared coherence function is widely used in many applications. The approximate confidence interval is only reliable for large data segments. In this letter, an iterative algorithm is provided to compute the exact confidence interval from the cumulative distribution function. In order to use the confidence interval conveniently in practice, some libraries are provided, using the iterative algorithm and cubic spline interpolation.

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Published date: March 2004
Organisations: Human Sciences Group

Identifiers

Local EPrints ID: 46599
URI: https://eprints.soton.ac.uk/id/eprint/46599
PURE UUID: 4369c090-e56c-4e5e-b86c-142cbcf881a5

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Date deposited: 19 Jul 2007
Last modified: 13 Mar 2019 21:02

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