  Understanding active electrolocation in weakly electric fish remains a
challenging issue. In this article we propose a mathematical formulation of
this problem, in terms of partial differential equations. This allows us to
detail two algorithms: one for localizing a target using the multi-frequency
aspect of the signal, and antoher one for identifying the shape of this target.
Shape recognition is designed in a machine learning point of view, and take
advantage of both the multi-frequency setup and the movement of the fish around
its prey. Numerical simulations are shown for the computation of the electric
field emitted and sensed by the fish; they are then used as an input for the
two algorithms.
