@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}, }