Open AccessPower law noise identification using the lag 1 autocorrelation
Author(s) -
William Riley,
C.A. Greenhal
Publication year - 2004
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1049/cp:20040932
Subject(s) - autocorrelation , lag , noise (video) , autocorrelation technique , identification (biology) , noise measurement , computer science , mathematics , electronic engineering , statistics , engineering , noise reduction , artificial intelligence , image (mathematics) , biology , computer network , botany
This paper describes a new method for power law noise identification, based on the lag 1 autocorrelation function, that can determine the dominant noise type for all common noise processes, from phase or frequency data, for all averaging factors, in a consistent and analytic manner. ρ µ µ σ k tt k
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