  We introduce a new pattern recognition algorithm for track finding in High
Energy Physics Experiments based on an extension of the Hough Transform to
multiple dimensions. A remarkable property of this algorithm is that the
execution time is simply proportional to the total number of the hits to be
processed, making it particularly attractive for high occupancy situations. The
algorithm needs to be trained using a sufficiently large set of simulated
tracks. The same track finding algorithm can be used for very different
detector geometries and only the set of simulated tracks used for training
needs to be changed. The particular structure of the algorithm also lends
itself naturally to parallel hardware implementations which, combined with its
intrinsic flexibility, should provide a most powerful tool for triggering at
future colliders.
