Utilizing spatial statistical models to reduce data redundancy and entropy
OwnerAdam Jeffriesinventor
Life of this patent
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Abstract
A method, article comprising machine-readable instructions and apparatus that processes data systems for encoding, decoding, pattern recognition/matching and data generation is disclosed. State subsets of a data system are identified for the efficient processing of data based, at least in part, on the data system's systemic characteristics.
Claims20
A system comprising:
- a processing device;
- a non-transitory, tangible medium that stores instructions that when executed by the processing device cause the system to perform operations comprising:
- accessing a value corresponding to a point comprised by a space of a spatial probability model, the point corresponding to a state comprised by a state superset of at least one of the following:
- a data system or a systemic characteristic of the data system;
- determining an output based at least in part on the value corresponding to the point comprised by the space of the spatial probability model, the output corresponding to at least one of the following:
- a boundary of a state subset, the state subset comprising a subset of states of the state superset, or
- a probability of the state comprised by the state superset of:
- the data system or the systemic characteristic of the data system;
- using the output corresponding to at least one of the state subset or the probability of the state, to construct data with reduced redundancy and/or reduced average information entropy;
- using the data with reduced redundancy and/or reduced average information entropy to perform at least one of the following:
- generating and transmitting a message comprising the data with reduced redundancy and/or reduced average information entropy, or
- generating and storing a computer file comprising the data with reduced redundancy and/or reduced average information entropy.
The system of claim 12, the method further comprising implementing, by the data processor, a hierarchical multi-resolution structure for the space and/or the output sequence.
The system of claim 12, wherein the sequence function comprises at least a mathematical monotonically increasing function, a summation function, a multiplication function, a delta function, a trigonometric function, a lexicographic ordering function, a sorting function, or a sequence function that generates a delta value of the output sequence that is a measure of a variance from a determined value.
The system of claim 12, wherein the ordered sequence of data elements includes at least sixty-four bits.
A method comprising:
- accessing, by a data processor comprising hardware, a value corresponding to a point comprised by a space of a spatial probability model, the point corresponding to a state comprised by a state superset of at least one of the following:
- a data system or a systemic characteristic of the data system;
- determining, by the data processor, an output based at least in part on the value corresponding to the point comprised by the space of the spatial probability model, the output corresponding to at least one of the following:
- a boundary of a state subset, the state subset comprising a subset of states of the state superset, or
- a probability of the state comprised by the state superset of:
- the data system or the systemic characteristic of the data system;
- using the output corresponding to at least one of the boundary of the state subset or the probability of the state, to construct, by the data processor, data with reduced redundancy and/or reduced average information entropy;
- using the data with reduced redundancy and/or reduced average information entropy to perform at least one of the following:
- generating and transmitting a message comprising the data with reduced redundancy and/or reduced average information entropy, or
- generating and storing a computer file comprising the data with reduced redundancy and/or reduced average information entropy, or
- generating an analysis of the data with reduced redundancy and/or reduced average information entropy.
Dependencies are inferred from the claim text.