Photoplethysmography Biometric Recognition Model Based on Sparse Softmax Vector and <i>k</i>-Nearest Neighbor

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Process</td><td class="align_center">Time (s)</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Preprocessing</td><td class="align_center">0.0001</td></tr><tr><td class="align_left">Feature extraction</td><td class="align_center">0.4421</td></tr><tr><td class="align_left">Matching</td><td class="align_center">0.0013</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Time costs of the proposed method.</div>

Journal of Electrical and Computer Engineering

tab7

Table 7

Table 7: Photoplethysmography Biometric Recognition Model Based on Sparse Softmax Vector and <i>k</i>-Nearest Neighbor 

Journal of Electrical and Computer Engineering

Photoplethysmography Biometric Recognition Model Based on Sparse Softmax Vector and k-Nearest Neighbor

Table 7