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Manimegalai, P.
- Mental State Recognition by using Brain Waves
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Authors
Affiliations
1 ECE Department, Karpagam University, Coimbatore - 641021, Tamil Nadu, IN
2 Department of EIE, BIT, Bangalore - 560004, Karnataka, IN
3 ECE Department, Karpagam University, Coimbatore - 641021, Tamil Nadu
1 ECE Department, Karpagam University, Coimbatore - 641021, Tamil Nadu, IN
2 Department of EIE, BIT, Bangalore - 560004, Karnataka, IN
3 ECE Department, Karpagam University, Coimbatore - 641021, Tamil Nadu
Source
Indian Journal of Science and Technology, Vol 9, No 33 (2016), Pagination:Abstract
Mental State classification plays vital role in communication between human and computer. It can be classified by brain waves. Brain signals recording methods along scalp are invasive and non-invasive. The advanced common method is noninvasive. The 10-10 and 10-20 electrodes system standards are used in the non-invasive method. It is aimed to find Mental State of a sample by using EEG signals. In this work EEG sample are collected from the DEAP database. 30 preprocessed EEG signals from DEAP data sets are worked to get different frequency band by Welch method. Power spectral density in alpha and beta band is tabulated. The valence arousal points from the pre-processed data is obtained from the matlab files Four mental states are classified as four quadrants of graph. 30 participants are classified into four mental states namely happy, stressed, depressed and relaxed in MATLAB. As result four mental states are classified as four quadrants of graph.Keywords
BCI, EEG, MS, MS PSD- Development of Artificial Intelligent Skills and Techniques in Agricultural Robotics
Abstract Views :160 |
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Authors
Affiliations
1 Karpagam University, Coimbatore − 641021, IN
2 RPRC Department of CSE, Dr Ambedkar Institute of Technology, Near Jnana Bharathi Campus, Bengaluru 560056, Karnataka, IN
1 Karpagam University, Coimbatore − 641021, IN
2 RPRC Department of CSE, Dr Ambedkar Institute of Technology, Near Jnana Bharathi Campus, Bengaluru 560056, Karnataka, IN
Source
Indian Journal of Science and Technology, Vol 9, No 45 (2016), Pagination:Abstract
Objectives: This analysis paper mainly focuses on the development of cognitive architecture where the agents at different levels exhibit different levels of thinking and on the acquisition of smart sensor motor skills which is known as Construction Skill Tree (CST). Methods/Statistical Analysis: These concepts are implemented through simulation by using prolog programming language. This simulation is an imitation of the operation of real world fruit picking robot system over time. It includes the discovery of one’s own body, including its structure and dynamics. This includes the acquisition of associated cognitive skills such as self and non-self-distinction. Finding: The obtained simulation results can be given by designing and implementing the Construction Skill tree Implementation Architecture (CSIA). The design of CSIA provides faster skill acquisition. Hence it is called CSIA, the CSIA has a five layer and first four layers are single agent environment. Improvement/Application: The proposed cognitive architecture has collections of agents that work together for reaching predefined goal. In CSIA these contains reflexive, reactive, deliberative, thinking and meta-thinking layer.Keywords
Agent, Construction Skill tree Implementation Architecture (CSIA), Cognitive Architecture, Smart Fruit Picking Robots.- Conceptual Improvisation on Low Power Mitigation for Domino Logic Systems using CHSK Domino Logic
Abstract Views :172 |
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Authors
Affiliations
1 Department of Electronics and Communication Engineering Karpagam University, Pollachi Main Road, L & T By Pass Road Junction, Eachanari Post, Eachanari, Coimbatore – 641021, Tamil Nadu, IN
1 Department of Electronics and Communication Engineering Karpagam University, Pollachi Main Road, L & T By Pass Road Junction, Eachanari Post, Eachanari, Coimbatore – 641021, Tamil Nadu, IN