Teknologi Indonesia
Vol 36, No 1 (2013)

SEQUENTIAL EXTENDED KALMAN FILTER ON EEG EXTRACTION AND CLASSIFICATION

Turnip, Arjon (Unknown)
Soetraprawata, Demi (Unknown)
Hariyadi, - (Unknown)
Kusumandari, Dwi Esti (Unknown)

Article Info

Publish Date
17 Feb 2015

Abstract

In this paper, a neural networks training based on Sequential Extended Kalman Filtering (SEKF) analysis for extraction and classifi cation of recorded EEG signal is proposed to improved feature extraction, classifi cation accuracy,and communication rate as well. The robustness of the SEKF against background noises has been evaluated by comparing the separation performance indices of the SEKF with well known algorithms (i.e., BPNN, JADE,and SOBI). A statistically signifi cant improvement was achieved with respect to the rates provided by raw data.

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Journal Info
Teknologi Indonesia
Website

Abbrev

JTI

Publisher

Lembaga Ilmu Pengetahuan Indonesia

Subject

Computer Science & IT

Description

JTI is a journal in the Departement of Engineering Sciences - Indonesian Institute of Sciences (LIPI). JTI has policy to publish a new and original research paper or a review paper in The scope of Technology. JTI publishes two issues per year. The journal has been registered with printed-ISSN ...