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Radio Frequency IDentification (RFID) is a non-contact technology that uses radio frequency electromagnetic fields to transfer data from a tag attached to an object, for the purposes of automatic identification and tracking. One of the common problems that arise in any RFID deployment is the collision between tags which reduces the efficiency of the RFID system. Dynamic Framed-Slotted ALOHA (DFSA) is one of the most popular approaches to resolve the tag collision problem. In this paper, the authors propose an accurate maximum a posteriori (MAP)-based tag estimation method with low computational complexity. The idea behind their method is to more accurately determine the most potential number of tags which draws the observed results on the basis of both a posteriori probability and a priori probability.
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