Abstract

AbstractA simple algorithm for deconvolution and regression of shot‐noise‐limited data is illustrated in this paper. The algorithm is easily adapted to almost any model and converges to the global optimum. Multiple‐component spectrum regression, spectrum deconvolution and smoothing examples are used to illustrate the algorithm. The algorithm and a method for determining uncertainties in the parameters based on the Fisher information matrix are given and illustrated with three examples. An experimental example of spectrograph grating order compensation of a diode array solar spectroradiometer is given to illustrate the use of this technique in environmental analysis. The major advantages of the EM algorithm are found to be its stability, simplicity, conservation of data magnitude and guaranteed convergence.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.