Abstract
There are a kind of non-linear filters in the active detection problem solution which can weaken the bigger and strengthen the smaller samples, that can be called as Gaussianization, and to improve performance of subsequent correlation test. An explicit definition about this kind of nonlinear Gaussianization filter is given at first. In succession, the two typical nonlinear filters are proposed and studied. One is U-filter, based on the probability density function and its derivate. The other is G-filter, based on the cumulative distribution function and its inverse. Instances with lake trial data are illustrated to test these two methods' performance.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
