1. A method, comprising: receiving a set of signal observations for a signal repetition, wherein the set of signal observations is associated with a dimension of a K-dimensional time grid having a plurality of time-indexed points; calculating a state cost metric for a state in a plurality of states of a statistical model, for a given time-indexed point, wherein the state cost metric calculation provides a most-likely predecessor state and a corresponding most-likely predecessor time-indexed point; determining a sequence of states using the state cost metric calculation; determining a corresponding cumulative probability measure for the statistical model; calculating a cost metric associated with a possible prior state at a possible predecessor time-indexed point; selecting a lowest cost metric for the state to determine the state cost metric; observing dimensions that are incremented when moving from a given predecessor time-index point to a given one of the plurality of time-indexed points; and basing the state cost metric on at least the observing.