EEG refers to the recording of the brain’s spontaneous electrical activity over a short period of time, usually 20–40 minutes, as recorded from multiple electrodes placed on the scalp. In advance EEG signals used to be a first-line method for the diagnosis of tumors, stroke and other focal brain disorders. The structure generating the signal is not simply linear, but also involves nonlinear contributions [7, 8, 9].These non-stationary signals are may contain indicators of current disease, or even warnings about impending diseases. This work aims at providing new insights on the Electroencephalography (EEG) fragmentation problem using wavelets [2, 5]. The present work describes a computer model to provide a more accurate picture of the EEG signal processing via Wavelet Transform [16, 17, 18, 19]. The Matlab techniques have been uses which provide a system oriented scientific decision making modal [16, 17]. Within this practice the applied signal has been compared in a sequential order with dissimilar cases in attendance in the database. Special EEG signals have been considered from Physio bank  and Vijaya Medical Centre, Visakhapatnam, India. Analyze the signal under consideration and renowned the holder 100% truthfully.
RamaRaju, P. V. Mr.; Rao., V.Malleswara; and AnogjnaAurora, N.
"Incursion Model for Nomenclature of EEG Signals via Wavelet Transform,"
International Journal of Communication Networks and Security: Vol. 1
, Article 7.
Available at: https://www.interscience.in/ijcns/vol1/iss1/7