Evaluation of a High-Accuracy Indoor-Positioning System with Wi-Fi Time of Flight (ToF) and Deep Learning

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Hyperparameters</td><td class="align_center">Values</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Batch size</td><td class="align_center">10</td></tr><tr><td class="align_left">Number of epochs</td><td class="align_center">1000</td></tr><tr><td class="align_left">Hidden layer</td><td class="align_center">6</td></tr><tr><td class="align_left">Neuron in hidden layer</td><td class="align_center">128, 64, 32, 16, 8, and 4</td></tr><tr><td class="align_left"><i>η</i></td><td class="align_center">0.001</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The hyperparameter settings of our model.</div>

Journal of Computer Networks and Communications

tab5

Table 5

Table 5: Evaluation of a High-Accuracy Indoor-Positioning System with Wi-Fi Time of Flight (ToF) and Deep Learning 