Drowsiness analysis using common spatial pattern and extreme learning machine based on electroencephalogram signal
نویسندگان
چکیده
منابع مشابه
Simulation of Scour Pattern Around Cross-Vane Structures Using Outlier Robust Extreme Learning Machine
In this research, the scour hole depth at the downstream of cross-vane structures with different shapes (i.e., J, I, U, and W) was simulated utilizing a modern artificial intelligence method entitled "Outlier Robust Extreme Learning Machine (ORELM)". The observational data were divided into two groups: training (70%) and test (30%). Then, using the input parameters including the ratio of the st...
متن کاملExtreme Learning Machine for Graph Signal Processing
In this article, we improve extreme learning machines for regression tasks using a graph signal processing based regularization. We assume that the target signal for prediction or regression is a graph signal. With this assumption, we use the regularization to enforce that the output of an extreme learning machine is smooth over a given graph. Simulation results with real data confirm that such...
متن کاملModeling Discharge Coefficient of Side Weir on Converging Channel Using Extreme Learning Machine
In this study, the discharge coefficient of side weirs located on converging channels was simulated for the first time using a new method of Extreme Learning Machine (ELM). To examine the accuracy of the numerical model, the Monte Carlo simulations were used and the experimental values validation was conducted by the k-fold cross validation method. Then, the input parameters were detected for s...
متن کاملVowel Imagery Decoding toward Silent Speech BCI Using Extreme Learning Machine with Electroencephalogram
The purpose of this study is to classify EEG data on imagined speech in a single trial. We recorded EEG data while five subjects imagined different vowels, /a/, /e/, /i/, /o/, and /u/. We divided each single trial dataset into thirty segments and extracted features (mean, variance, standard deviation, and skewness) from all segments. To reduce the dimension of the feature vector, we applied a f...
متن کاملExtreme learning machine based supervised subspace learning
This paper proposes a novel method for supervised subspace learning based on Single-hidden Layer Feedforward Neural networks. The proposed method calculates appropriate network target vectors by formulating a Bayesian model exploiting both the labeling information available for the training data and geometric properties of the training data, when represented in the feature space determined by t...
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: Journal of Medical Signals & Sensors
سال: 2019
ISSN: 2228-7477
DOI: 10.4103/jmss.jmss_54_18