Special Object Recognition Based on Sparse Representation in Multisource Data Fusion Samples

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td class="align_left">SNR (dB)</td><td class="align_center">5</td><td class="align_center">10</td><td class="align_center">15</td><td class="align_center">20</td><td class="align_center">25</td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td class="align_left">Number of human</td><td class="align_center" colspan="5">1</td></tr><tr><td class="align_left">Number of animals</td><td class="align_center" colspan="5">1 or 3</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Parameter settings for experiment 3.</div>

Mathematical Problems in Engineering

tab4

Table 4

Table 4: Special Object Recognition Based on Sparse Representation in Multisource Data Fusion Samples 