Methods and systems for data analysis and feature recognition

A system for data analysis and feature recognition comprising:

• a computer processor;
• a display in communication with the computer processor;
• a data store in communication with the computer processor, the data store containing a series of algorithms;
• a first digital data set in communication with the processor, the first digital data set comprising a plurality of subsets, each of the plurality of subsets being drawn from a different band of a frequency spectrum;
• a second digital data set in communication with the processor, the second digital data set comprising a plurality of subsets, each of the plurality of subsets being drawn from a different band of a frequency spectrum;
• and
• a memory in communication with the computer processor and containing stored programming instructions operable by the computer processor, the stored programming instruction, when operated by the computer processor, causing the computer processor to:
• TRAIN FOR THE PRESENCE OF THE FEATURE WITHIN THE FIRST DIGITAL DATA SET BASED ON THE SERIES OF ALGORITHMS, COMPRISING:
• (x) calculating a first value for a first target data element within a first subset from the plurality of subsets within the first digital data set using one of the algorithms from the series of algorithms;
• (xi) calculating a second value for a second target data element within a second subset from the plurality of subsets within the first digital data set using one of the algorithms from the series of algorithms;
• (xii) repeating the steps of calculating the first value and calculating the second value for a plurality of additional target data elements within first subset and the second subset from the first digital data set;
• (xiii) defining a plurality of synaptic paths, each one of the plurality of synaptic paths being defined by the calculated first values and calculated second values for each of the target data elements;
• and
• (xiv) associating the feature with one or more of the synaptic paths;
• and
• IDENTIFY THE FEATURE IN THE SECOND DIGITAL DATA SET BASED ON THE SERIES OF ALGORITHMS, COMPRISING:
• (xv) calculating a first value for a first target data element within a first subset from the plurality of subsets within the second digital data set using one of the algorithms from the series of algorithms;
• (xvi) calculating a second value for a second target data element within a second subset from the plurality of subsets within the second digital data set using one of the algorithms from the series of algorithms;
• (xvii) repeating the steps of calculating the first value and calculating the second value for a plurality of additional target data elements within the second digital data set using the first algorithm and the second algorithm from the series of algorithms;
• and
• (xviii) determining whether the feature is present in the second digital data set by comparing the calculated first values and second values from the second digital data set with the defined plurality of synaptic paths associated with the feature.