کنفرانس مهندسی برق ایران

صفحه اصلی / سی و یکمین کنفرانس بین المللی مهندسی برق

Kernel-Based Embedded Feature Selection for Motor Imagery Based BCI

نویسندگان :

Mehdi Kamandar¹

1- دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته

کلمات کلیدی :

Brain–computer interface (BCI)،Electroencephalogram (EEG)،(Motor imagery (MI،)،Support vector machine (SVM)،Kernel-target alignment (KTA)،Embedded feature selection،l1 regularization،minibatch proximal gradient ascent

چکیده :

Brain-computer interface (BCI) based on motor imagery (MI) classification using scalp recorded multi-channel EEG signal play a major role in the control of artificial limbs and machines by people with severe disabilities. The most popular features are band power of EEG signals in frequency sub-bands in a relatively wide frequency band (e. g., 8-30 Hz) in different time windows of imagination period. The effectiveness of these features is highly dependent on the sub-bands and time windows adopted, since the optimal sub-bands and time windows is generally subject-specific. The nonlinear support vector machine (SVM) with Gaussian kernel is an excellent classifier for MI classification. In this paper, the SVM with an anisotropic Gaussian kernel with a special scaling factors for each feature is used, instead of one scale factor for all features. The scaling factors are tuned by maximizing the kernel-target alignment criterion with l1 regularization. Some of the scaling factors will be zero after maximization due to l1 regularization, that is equivalent to removing corresponding features from classification processes. Therefore, an embedded feature selection is also done to remove the destructive effect of irrelevant and redundant features. The average accuracy of the SVM classifier with anisotropic Gaussian kernel for four subjects in BCI IV-1 dataset is about 10% more than the SVM with isotropic Gaussian kernel.

لیست مقالات

لیست مقالات بایگانی شده

Unsupervised Change Detection in SAR Images Using a Six-Branch CNN and Adaptive Window Approach

Abbas Kakoolvand - Maryam Imani - Hassan Ghassemian

Scattering by an array of PEC cylinders in ferrite media using spectral technique

Zahra Bahrami - Asghar Keshtkar - Ayaz Ghorbani

Robust H∞ Control Design for Variable-Speed Wind Turbines Using Bilinear Matrix Inequalities

Hamidreza Javanmardi - Alireza Hamedi - Mahya Rahimzadeh

A New High Voltage Gain Non-isolated DC-DC Converter

Ahmadreza Ghanaatian - Reza Takarli - Abolfazl Vahedi

ارزش گذاری منابع تولید پراکنده به منظور توسعه شبکه توزیع برق به کمک نظریه بازی‌ها

شایان مرادیان - حبیب رجبی مشهدی

Significant Methods to Improve Control of Quadrotors, Hexarotors and Octorotors

Peyman Amiri - Nima Sina - Mohammad Danesh

Job Title Prediction from Tweets Using Word Embedding and Deep Neural Networks

Shayan Vassef - Ramin Toosi - Mohammad Ali Akhaee

Design and Simulation of a Novel High Sensitive MEMS Microphone Based On a Spring-Supported Circular Diaphragm

Mehdi Pazhooh - Ebrahim Abbaspour-Sani

Proposed Small Signal Dynamic Model for a Grid-Connected Battery Storage System

Zahra Moradi- Shahrbabak

Exploring Different Machine Learning-based Methods for Learning the Language of Shepna Stock Price

Zoreh Ansari - Jalal Raeisi Gahruei - Mansoor Khademi

بیشتر

ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.8.0