EEG is a record of electronic signals of brain. If there are effective methods for analysis of EEG signal it can be used as a diagnostic tool for diseases related to brain function. We developed a new diagnostic system for analysis of EEG by using nonlinear dynamic theory.

We made a basic computer program which was designed to analysis of pattern of EEG. For analysis of pattern, EEG signal was processed by variable experimental analytical methods and grouped by common pattern.

Program was composed of multiple systems. Signal generating system was composed of Lorenz signal generation and Rossler signal generation parts. EEG processing system was composed of Normalization, Band pass filtering, First Second difference, Add random noise and Sur-rogate making parts. EEG analyses system was composed of Spectral analyses, Phase space analyses, Correlation analyses and Mode analyses parts. Pattern recognition and grouping system was com-posed of data format, Power spectrum, Neural network process and Classification parts.

We developed a basic computer program for systemic analysis of EEG by Nonlinear analysis methods.