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README -------- Directory contains the following files. 1. ADABOOST_te.m2. ADABOOST_tr.m3. demo.m4. likelihood2class.m5. threshold_te.m6. threshold_tr.m The aim of the project is to provide a source of themeta-learning algorithm known as AdaBoost to improvethe performance of the user-defined classifiers. To make use of adaboost, first two functions must berun with the appropriate parameters. The explanationof each source file is available with "help" command. To see how they work, run demo.m as ...
M.R.Ebenezar jebarani1and T.Jayanthy2 ABSTRACTIn Wireless sensor network, since the media is wireless there will be burst errors which leads tohigh bit error rate that affect the throughput. Wireless sensor networks drop the packets due to propagationerrors that lead to retransmission traffic. This paper evaluates the effect of adaptive FEC in Wirelesssensor networks. Adaptive FEC technique improves the throughput by dynamically tuning FEC dependingupon the wireless channel loss. The main ...
Title: AFEC: An Adaptive Forward Error- Correction Protocol and Its Analysis Author(S) :Kihong Park Journal/Conference Name: Computer Science Technical Reports :Volume Year: 1997 :Issue :Pages در صورت بروز مشکل در دانلود مقاله یا سوال با آدرس ایمیل projectsara.ir@gmail.com مکاتبه نمایید. با تشکر ...