Novel Rehab Devices’ Feature Extraction Analysis Using EMG Signal via Self-Organizing Maps (SOM)

2016 ◽  
pp. 175-184
Author(s):  
Zul Hasrizal Bohari ◽  
Mohd Hafiz Jali ◽  
Tarmizi Ahmad Izzuddin ◽  
Mohamad Na’im Mohd Nasir
Keyword(s):  
Feature Extraction ◽  
Self Organizing Maps ◽  
Emg Signal ◽  
Self Organizing

scholarly journals Feature Extraction of Structures in Sea Water Using Self-Organizing Maps and Electromagnetic Waves

2016 ◽  
Vol 16 (3) ◽  
pp. 261
Author(s):  
Murilo Teixeira Silva ◽  
Lurimar Smera Batista ◽  
Frederico Medeiros Vasconcelos De Albuquerque
Keyword(s):  
Feature Extraction ◽  
Electromagnetic Waves ◽  
Sea Water ◽  
Low Frequency ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
Virtual Sensors ◽  
Study Region ◽  
Direct Model ◽  
Self Organizing

<pre><!--StartFragment-->The use of Self-Organizing Map (<span>SOM</span>) algorithm for feature extraction and dimensionality reduction applied to underwater object detection with Low Frequency Electromagnetic Waves is presented. Computer simulation is used to generate a direct model for the study region, and a Self Organizing Map Algorithm is used to fit the data and return a similar model, with smaller dimensionality and same characteristics. Results show that virtual sensors are created by the <span>SOM</span> algorithm with consistent predictions, filling the resolution gap of the input data. These results are useful for fastening decision making algorithms by reducing the number of inputs to a group of significant data.<!--EndFragment--></pre>

A Psychographic Segmentation of Kuwaiti Travelers Using Self-Organizing Maps

2019 ◽  
Vol 24 (1) ◽  
pp. 87-92 ◽  
Author(s):  
Yvette Reisinger ◽  
Mohamed M. Mostafa ◽  
John P. Hayes
Keyword(s):  
Self Organizing Maps ◽  
Self Organizing
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