1. A method of tagging signals of interest in time variant data, the method causing a computing device to perform steps comprising: classifying, via a processor, data from an input signal using a short-term classifier, wherein there are at least two classifications available comprising a first classification of the data as having no identified outputs and a second classification of the data as at least one potential signal of interest, wherein the short-term classifier also bypasses data that is known to be of no interest; collapsing via the processor the input data in the short-term classifier that is classified as having no identified outputs, thereby creating time-variant data; and tagging via the processor a known signal of interest in the time-variant data that was classified as having at least one potential signal of interest.
1. A method of tagging signals of interest in time variant data, the method causing a computing device to perform steps comprising: classifying, via a processor, data from an input signal using a short-term classifier, wherein there are at least two classifications available comprising a first classification of the data as having no identified outputs and a second classification of the data as at least one potential signal of interest, wherein the short-term classifier also bypasses data that is known to be of no interest; collapsing via the processor the input data in the short-term classifier that is classified as having no identified outputs, thereby creating time-variant data; and tagging via the processor a known signal of interest in the time-variant data that was classified as having at least one potential signal of interest. 2. The method of claim 1 , wherein the tagging step causes the computing device to perform steps further comprising: tagging the time variant data as one of a known signal of interest or a potential signal of interest.