منابع مشابه
Sleep EEG Classification Using Fuzzy Logic
The computerized detection of multi stage system of EEG signals using fuzzy logic has been developed and tested on prerecorded data of the EEG of rats .The multistage detection system consists of three major stages: Awake, SWS (Slow wave sleep), REM (Rapid eye movement) which has been recorded and can be detected by the fuzzy classification and fuzzy rule base. The proposed work approaches to i...
متن کاملVoice and Unvoiced Classification Using Fuzzy Logic
In this paper, we proposed a system for automatic classification of speech. A speech signal contains three different regions voiced, unvoiced and silence. In the proposed system, Zero-Crossing rate and short term energy are used in a fuzzy logic control this classification. Arabic digits of the KSU database is used to test our proposed method. The proposed method achieves 2.5 % error between hu...
متن کاملRotation Invariant Texture Classification using Fuzzy Logic
In this paper, we develop a scale invariant texture classification method based on Fuzzy logic. It is applied for the classification of texture images. Texture is a common property of any surface having uncertainty. Two types of texture features are extracted one using Discrete Wavelet Transform (DWT) and other using Co-occurrence matrix. Co-occurrence features are obtained using DWT coefficien...
متن کاملScale Invariant Texture Classification using Fuzzy Logic
In this paper, scale invariant texture classification method based on Fuzzy logic is developed. It is applied for the classification of texture images. Two types of texture features are extracted one using Discrete Wavelet Transform (DWT) and other using Gray Level Co-occurrence matrix (GLCM). Two features are obtained from each sub-band of DWT coefficients up to fifth level of decomposition an...
متن کاملSleep Stages Classification Using Neural Network with Single Channel EEG
The usual method for sleep stages classification is visual inspection method by sleep specialist. It uses eight EEG channels (O1, O2, T3, T4, C3, C4, Fp1 and Fp2), EOG and also EMG for sleep analysis. This method consumes more time (hours) for sleep stages classification. Some brain disorders like narcolepsy (excessive day time sleepiness) requires real-time monitoring of sleep states which is ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advanced Research in Engineering
سال: 2015
ISSN: 2412-4362
DOI: 10.24178/ijare.2015.1.1.17