@article{(Open Science Index):https://publications.waset.org/pdf/9999464,
	  title     = {Wavelet Based Residual Method of Detecting GSM Signal Strength Fading},
	  author    = {Danladi Ali and  Onah Festus Iloabuchi},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, GSM signal strength was measured in
order to detect the type of the signal fading phenomenon using onedimensional
multilevel wavelet residual method and neural network
clustering to determine the average GSM signal strength received in
the study area. The wavelet residual method predicted that the GSM
signal experienced slow fading and attenuated with MSE of 3.875dB.
The neural network clustering revealed that mostly -75dB, -85dB and
-95dB were received. This means that the signal strength received in
the study is a weak signal.
},
	    journal   = {International Journal of Electronics and Communication Engineering},
	  volume    = {8},
	  number    = {9},
	  year      = {2014},
	  pages     = {1633 - 1636},
	  ee        = {https://publications.waset.org/pdf/9999464},
	  url   	= {https://publications.waset.org/vol/93},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 93, 2014},
	}