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Design and Analysis of a New Sequence Set by Using Chaotic Dynamic Systems for Spread Spectrum Communication Applications

Design and Analysis of a New Sequence Set by Using Chaotic D...

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2003 International Conference on Communication technology

作者： Mehrdad Abolbashari Hassan Aghaeinia Spread Spectrum Communication Research Laboratory Electrical Engineering Department Amirkabir University of Technology TehranIran assistant professor at department of electrical engineering amirkabir university of technology tehran Iran

In this paper some properties of sequence derived from proposed chaotic dynamic systems, are evaluated and analyzed. First, sequence has been investigated as a sequence with real values. It’s followed

关键词： Spreading Sequence Chaotic Dynamic System Merit Factor W-Index Asynchronous DS-CDMA System

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Effective Feature Selection for Short-term Earthquake Prediction Using NeuroFuzzy Classifier

Effective Feature Selection for Short-term Earthquake Predic...

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2010 Second IITA International Conference on Geoscience and Remote Sensing (IITA-GRS 2010)

作者： Leila Dehbozorgi Fardad Farokhi Scientific Association of electrical and Electronic engineering Islamic Azad University Centran Tehrasn Branch assistant professor electrical engineering Department Electrical Engineering Islamic Azad UniversityCentral Tehran Branch

Earthquakes is a serious sudden life threatening disaster for all kind of livings. Loss of life,property and depression are some common results of earthquakes for humankinds. The most important matter in this field is to predict earthquake time and strength. This study investigates an application of Neuro-Fuzzy classifier for short-term earthquake prediction using saved seismogram data. This method is able to predict earthquakes five minute before,with an acceptable accuracy （82.8571%）. The features were obtained from statistical and entropy parameters,Discrete Wavelet Transform （DWT）,Fast Fourier Transform （FFT）,Chaotic Features （Maximum Lyapunov Exponent）,estimated power spectral density （PSD）,and the classifier used this extracted features to indicate whether the earthquake were takes place in the next following five minutes or not. Finally,after training of Neuro-Fuzzy classifier effective features were selected with UTA [1] algorithm.

关键词： Earthquake prediction Short-term prediction Neuro-Fuzzy Classifier Discrete Wavelet Transform (DWT) Feature Selection Maximum Lyapunov Exponent

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