Intelligent Monitoring System Based on Noise-Assisted Multivariate Empirical Mode Decomposition Feature Extraction and Neural Networks

<table class="table-group" id="tab6"><tr><td><table class="table"><tr><td class="thead-hr" colspan="12"><hr/></td></tr><tr class="thead"><td class="align_left">Feature</td><td class="align_center"><span style="width: 21.0308ptpx;"><svg height="11.927pt" id="M116" style="vertical-align:-3.291101pt" version="1.1" viewbox="-0.0498162 -8.6359 21.0308 11.927" width="21.0308pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M686 28C612 35 607 44 591 112C563 234 541 360 519 489L489 666L457 658L147 121C100 40 89 36 24 28L17 0H240L250 28C168 34 159 41 190 101L262 237H482C495 180 503 137 510 91C517 47 514 35 441 28L433 0H677L686 28ZM475 280H285L429 541H431L475 280Z"></path></g><g transform="matrix(.013,0,0,-0.013,9.135,0)"><path d="M584 650H137L131 622C214 614 217 612 200 521L125 127C109 41 101 35 23 28L17 0H288L294 28C201 35 193 42 209 128L242 309H348C440 309 442 300 443 226H471L510 422H482C452 354 449 348 357 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class="align_center">0.741</td><td class="align_center">0.603</td><td class="align_center">0.402</td><td class="align_center"><svg height="8.89449pt" id="M127" style="vertical-align:-1.11981pt" version="1.1" viewbox="-0.0498162 -7.77468 7.75925 8.89449" width="7.75925pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M531 71V127L115 310L531 494V550L57 335V285L531 71ZM531 -40V10H57V-40H531Z"></path></g></svg>0.1</td></tr><tr class="table-tr"><td colspan="12"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Discrimination criterion for the proposed features.</div>

Computational Intelligence and Neuroscience

tab6

Table 6

Table 6: Intelligent Monitoring System Based on Noise-Assisted Multivariate Empirical Mode Decomposition Feature Extraction and Neural Networks 