Abstract

Automatic target generation process (ATGP) has been found very useful and effective for unsupervised target detection. It performs a sequence of orthogonal subspace projection to extract potential targets of interest. One major issue arises in ATGP is how to terminate the algorithm in the sense that how many targets are required for ATGP to generate before it is terminated. This paper presents a recursive version of ATGP, referred to as recursive ATGP (RATGP) which has two advantages. One is no need of inverting any matrix as ATGP does for finding each target. Most importantly, a stopping rule can be derived for ATGP via RATGP is also developed using the Neyman-Pearosn detection theory to determine how many targets needed to be generated by RATGP before it is terminated.

Full Text
Paper version not known

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.