A computationally efficient nonlinear least squares method using random basis functions

Authors

Steven Kay, University of Rhode Island

Document Type

Article

Date of Original Version

6-21-2013

Abstract

A method to obtain parameter estimates in a nonlinear least squares problem is proposed. Its main advantage is computational efficiency and can be used when a direct grid search cannot. The approach is based on the theory of random basis functions. An example of its application to frequency estimation is given and other applications discussed. © 1994-2012 IEEE.

Publication Title, e.g., Journal

IEEE Signal Processing Letters

Volume

20

Issue

7

Citation/Publisher Attribution

Kay, Steven. "A computationally efficient nonlinear least squares method using random basis functions." IEEE Signal Processing Letters 20, 7 (2013): 721-724. doi: 10.1109/LSP.2013.2264808.