The Alpha-Beta Log-Det divergences for positive definite matrices are flexible divergences that are parameterized by two real constants and are able to specialize several relevant classical cases like the squared Riemannian metric, the Steins loss, the S-divergence, etc. A novel classification criterion based on these divergences is optimized to address the problem of classification of the moto...

In this paper, we propose an improved filter selection method using Welch’s t-test based on discriminative filter bank common spatial pattern (DFBCSP). Existing DFBCSP used the Fisher ratio in order to find out discriminative filters. However, the Fisher ratio can be used to know only comparative value of distinguishability but may not become a meaningful criterion to reject null hypothesis. As...

iranian traditional cities were created with a system based on experiments and gradual establishment of society through time. qajar era is especially important in iranian art history. until mid qajar era, iranian cities’s architecture mainly took benefit of its common traditional architecture that is already seen in most desert-surrounding cities. till this era, there was not any connection bet...

the present study aims to simulate the spatial pattern of land use change in lisar protected area,iran. land cover maps for 1989, 2000, and 2007 were depicted using tm, etm+, and irs liss-iii images ofthe area at stake. images were classified using a merge of unsupervised and supervised classification. camarkov model was used to predict land cover maps as a top-down approach in investigating la...

In some tasks that require sustained attention, vigilance levels of the operator might become very important. EEG has been proved very effective for measuring vigilance. However, many difficulties exist in this field such as how to label the EEG data, how to remove the noise from the EEG data and so on. In this paper, we introduce a very useful signal transform method, Common Spatial Pattern, t...

The Common Spatial Pattern (CSP) algorithm is a popular method for calculating spatial lters in motor imagery braincomputer interface system. However, the performance of CSP is in uenced by several factors such as the selection of channels, time window length, frequency band and etc.. One of the existing problems is that some above parameters for CSP is tuned manually in most of papers in the l...

We propose a novel framework for the classification of single trial ElectroEncephaloGraphy (EEG), based on regularized logistic regression. Framed in this robust statistical framework no prior feature extraction or outlier removal is required. We present two variations of parameterizing the regression function: (a) with a full rank symmetric matrix coefficient and (b) as a difference of two ran...

Electroencephalogram (EEG) signals reflect the activities or electrical disturbances in neurons human brain. Therefore, these are vital for diagnosing certain brain disorders. This study mainly focused on diagnosis of epilepsy and autism spectrum disorders (ASDs) through analysis processing EEGs. In this study, artifacts were removed from EEG datasets using Independent Component Analysis filter...

Accurate binary classification of electroencephalography (EEG) signals is a challenging task for the development motor imagery (MI) brain–computer interface (BCI) systems. In this study, two sliding window techniques are proposed to enhance MI. The first one calculates longest consecutive repetition (LCR) sequence prediction all windows and named SW-LCR. second mode SW-Mode. Common spatial patt...