ters, curvelets, shearlets, ridgelets, wavelets, and learned filters), general Lipschitz-continuous non-linearities (e.g., rectified linear units, shifted logistic sigmoids, hyperbolic tangents, and modulus functions), and general Lipschitz-continuous pooling operators emulating, e.g., sub-sampling and averaging</p>
<ul>
<li><p>all of these elements can be different in different network layers.</p></li>
</ul>
</li>
<li><p>translation invariance result of vertical nature in the sense of the features becoming