Abstract
The fuzzy-set theory is used to synthesize an optimum linear meter for observations in the presence of correlated interferences. It is shown that replacement of the linear discriminator in the classical Kalman filter with a nonlinear discriminator based on calculation of fuzzy preference relations allows obtaining the optimum solution for observations performed in the presence of both correlated and uncorrelated interferences. The operability and efficiency of the synthesized meter are confirmed by the results of comparative simulation. The area of application of the synthesized meter comprises data processing systems with the dominating requirement of simple implementation.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Journal of Communications Technology and Electronics
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.