This paper describes a new technique to classify and analyze the electroencephalogram (EEG) signal and recognize the EEG signal characteristics of Sleep Apnea Syndrome (SAS) by using wavelet transforms and an artificial neural network (ANN). The EEG signals are separated into Delta, Theta, Alpha, and Beta spectral components by using multi-resolution wavelet transforms. These spectral component...

in this study, activated sludge process for wastewater treatment in a refinery was investigated. for such purpose, a laboratory scale rig was built. the effect of several parameters such as temperature, residence time, effect of leca (filling-in percentage of the reactor by leca) and uv radiation on cod removal efficiency were experimentally examined. maximum cod removal efficiency was obtained...

In the hydrological cycle, runoff precipitation is one of most significant and complex phenomena. order to develop improve predictive models, different perspectives have been presented in its modeling. Hydrological processes can be confidently modeled with help artificial intelligence techniques. this study, Leilanchai watershed was simulated using neural networks (ANNs) M5 model tree methods t...

Rainfall-Runoff models are mostly empirical in nature demanding the knowledge of a large number of catchment parameters. On the contrary Artificial Neural Networks (ANN) can be deployed in cases where the available data is limited. The present work involves the development of an ANN model using Backward Propagation algorithm. The hydrologic variables used were Rainfall, Soil Moisture, Evaporati...

The mortality rate due to breast cancer is increasing, for five minute a women dies worldwide. Mammogram is one which reduces the death rate by early diagnosis and regular screening. This paper hypothesize a consolidate approach of FPGA implementation for automatic detection of breast cancer and classification of the tumor by adopting 2D discrete wavelet transform and artificial neural network ...

large-scale climatic signals including ocean-atmosphere interactions, are the main factors influencing the earth’s climatic oscillations and are the most important indices in predicting of climate variables. in this research, precipitation in the next month was predicted by applying artificial neural network (ann), neuro-fuzzy network (nfn), and multiple linear regression (mlr) in semnan synopt...

This paper presents an alternative approach for signal detection and equalization using the continuous wavelet transform (CWT) and the artificial neural network (ANN) in diffuse indoor optical wireless links (OWL). The wavelet analysis is used for signal pre-processing (feature extraction) and the ANN for signal detection. Traditional receiver architectures based on matched filter (MF) experien...

This paper demonstrates classification of PQ events utilizing wavelet transform (WT) energy features by artificial neural network (ANN) and SVM classifiers. The proposed scheme utilizes wavelet based feature extraction to be used for the artificial neural networks in the classification. Six different PQ events are considered in this study. Three types of neural network classifiers such as feed ...