A New Adaptive LSSVR with Online Multikernel RBF Tuning to Evaluate Analog Circuit Performance

<table>Local regression curve of output <svg height="15.45" id="M185" style="vertical-align:-3.43848pt" version="1.1" viewbox="0 0 22.85 15.45" width="22.85" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<g transform="matrix(.012,-0,0,-.012,13.038,15.187)"><path d="M745 361q0 -166 -116 -272t-291 -106q-136 0 -225.5 83t-89.5 218q0 161 115.5 272t288.5 111q137 0 227.5 -83t90.5 -223zM643 359q0 126 -56 199.5t-167 73.5q-130 0 -213.5 -104t-83.5 -246q0 -117 58 -190.5t165 -73.5q91 0 160.5 52t103 128.5t33.5 160.5z" id="x1D442"></path></g>
</svg> and gain <svg height="16.6" id="M186" style="vertical-align:-3.50803pt" version="1.1" viewbox="0 0 59.962502 16.6" width="59.962502" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> with the three methods.</table>

Abstract and Applied Analysis

fig3

Figure 3

Figure 3: A New Adaptive LSSVR with Online Multikernel RBF Tuning to Evaluate Analog Circuit Performance 