Abstract
Measurement systems suffer from problems due to the imperfectness of sensory devices and measuring channels, and the shortage of available information concerning the investigated phenomena itself. This imperfectness and shortage result in unwanted alterations and perturbations of the measured values and/or signals. Better results can be achieved if these alterations and perturbations are counteracted. The role of the inverse algorithms is this counteraction in order to improve the quality of measurement. This paper deals with the challenging issue of addressing various complexity levels of inverse problems and provides solutions illustrated via different application examples.
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.
