000			01937cam a2200337 a 4500
003			EG-GiCUC
005			20250223031348.0
008			151206s2015 ua do f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.20.01.M.Sc.2015.Ah.M
100	0		_aAhmed Galal Ahmed Mohammed
245	1	0	_aMachine learning based spectrum sensing techniques in cognitive radio / _cAhmed Galal Ahmed Mohammed ; Supervised Reda Elkhoribi , Mahmoud Ahmed Ismail
246	1	5	_aاستشعار الطيف انترددى بإستخدام آليات انتعلم فى الراديو الإدراكى
260			_aCairo : _bAhmed Galal Ahmed Mohammed , _c2015
300			_a100 Leaves : _bcharts , photographs; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Computer and Information - Department of Information Technology
520			_aWe implement and design 8 digital modulations are: 2ASK, 2FSK, 4ASK, 4FSK, 2PSK, 4PSK, DPSK, and 16QAM. The maximum value of spectral density of normalized centered amplitude and the average value of normalized absolute centered instantaneous phase deviation choose as key features for digital modulation recognizer based on the ANN. We used the Rayleigh fading channel to model signals propagation and corrupted the signals by additive white gaussian noise (AWGN) for testing the algorithm. The simulation results show that the ANN could be recognized the different types of the PUs and corrected classify the signals in its current state of development
530			_aIssued also as CD
653		4	_aANN
653		4	_aDigital modulation
653		4	_aMultipath fading channel
700	0		_aMahmoud Ahmed Ismail , _eSupervisor
700	0		_aReda Elkhoribi , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c53769 _d53769