# US 2018/0025285 A1 · Utilizing spatial statistical models to reduce data redundancy and entropy > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0025285 A1 - Document ID: US20180025285A1 - Status: Published application - Kind: A1 - Application number: 15/721,143 - Filed: 2017-09-29 - Published: 2018-01-25 - Earliest claimed: 2012-03-04 - Inventors: Adam Jeffries - Web page: https://patentgrep.com/patent/US20180025285A1 ## CPC - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06F 16/284: {Relational databases} - H03M 7/3068: {Precoding preceding compression, e.g. Burrows-Wheeler transformation} - H03M 7/3079: {Context modeling} - H03M 7/70: {Type of the data to be coded, other than image and sound} - H04N 19/463: by compressing encoding parameters before transmission - H04N 19/91: Entropy coding, e.g. variable length coding [VLC] or arithmetic coding - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - H03M: CODING; DECODING; CODE CONVERSION IN GENERAL (using fluidic means F15C4/00; optical analogue/digital converters G02F7/00; coding, decoding or code conversion, specially adapted for particular applications, see the relevant subclasses, e.g. G01D, G01R, G06F, G06T, G09G, G10L, G11B, G11C, H04B, H04L, H04M, H04N; ciphering or deciphering for cryptography or other purposes involving the need for secrecy G09C) - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## 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. ## Claims ### Claim 1 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. ### Claim 2 (depends on 1) The system of claim 1, the operations further comprising: receiving the data system; using a sequence function that operates on an ordered sequence of data units from the data system to generate an output sequence; corresponding the output sequence to the point comprised by the space of the spatial probability model by employing a function that at least: determines a number of times the state, comprised by the state superset of the data system or state superset of the systemic characteristic of the data system, corresponds to the point comprised by the space, or determines a number of times data units of the output sequence correspond to the point comprised by the space, or determines a probability of the state, comprised by the state superset of the data system or the state superset of the systemic characteristic of the data system, corresponding to the point comprised by the space, or determines a range of probable sums of the ordered sequence of data units from the data system, or determines a probability distribution indicating the probability of the state, comprised by the state superset of the data system or comprised by the state superset of the systemic characteristic of the data system, corresponding to the point comprised by the space, or determines an identifier representing a state subset type, or determines an identifier enabling an assignment of the probability of the state, comprised by the state superset of the data system or comprised by the state superset of the systemic characteristic of the data system, corresponding to the point comprised by the space. ### Claim 3 (depends on 1) The system of claim 1, the operations further comprising supercorresponding at least two states of the state superset to a same point comprised by the space of the spatial probability model. ### Claim 4 (depends on 1) The system of claim 1, wherein the spatial probability model comprises at least a Euclidean space, a Non-Euclidean space, a topological space, or a phase space. ### Claim 5 (depends on 1) The system of claim 1, wherein the space of the spatial probability model comprises at least two dimensions. ### Claim 6 (depends on 12) 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. ### Claim 7 (depends on 1) The system of claim 1, the operations further comprising determining a location of the point comprised by the space in a continuous space. ### Claim 8 (depends on 12) 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. ### Claim 9 (depends on 12) The system of claim 12, wherein the ordered sequence of data elements includes at least sixty-four bits. ### Claim 10 (depends on 1) The system of claim 1, wherein the systemic characteristic of the data system corresponds to a structure, a unit of data, a data subsystem, a relationship between units or subsystems, a process, or a spatial form. ### Claim 11 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. ### Claim 12 (depends on 11) The method of claim 11, further comprising: receiving, by the data processor, the data system; using, by the data processor, a sequence function that operates on an ordered sequence of data units from the data system to generate an output sequence; corresponding, by the data processor, the output sequence to an element of the spatial probability model by employing a function that at least: determines a number of times the state, comprised by the state superset of the data system or state superset of the systemic characteristic of the data system, corresponds to the point comprised by the space, or determines a number of times data units of the output sequence correspond to the point comprised by the space, or determines a probability of the state, comprised by the state superset of the data system or the state superset of the systemic characteristic of the data system, corresponding to the point comprised by the space, or determines a range of probable sums of the ordered sequence of data units from the data system, or determines a probability distribution indicating the probability of the state, comprised by the state superset of the data system or comprised by the state superset of the systemic characteristic of the data system, corresponding to the point comprised by the space, or determines an identifier representing a state subset type, or determines an identifier enabling an assignment of the probability of the state, comprised by the state superset of the data system or comprised by the state superset of the systemic characteristic of the data system, corresponding to the point comprised by the space. ### Claim 13 (depends on 11) The method of claim 11, the method further comprising supercorresponding, by the data processor, at least two states of the state superset to a same point comprised by the space of the spatial probability model. ### Claim 14 (depends on 11) The method of claim 11, wherein the spatial probability model comprises at least a Euclidean space, a Non-Euclidean space, a topological space, or a phase space. ### Claim 15 (depends on 11) The method of claim 11, wherein the space of the spatial probability model comprises at least two dimensions. ### Claim 16 (depends on 12) The method 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. ### Claim 17 (depends on 12) The method 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. ### Claim 18 (depends on 12) The method of claim 12, wherein the ordered sequence of data elements includes at least sixty-four bits. ### Claim 19 (depends on 11) The method of claim 11, the method further comprising determining a location of the point comprised by the space in a continuous space. ### Claim 20 (depends on 11) The method of claim 11, wherein the systemic characteristic of the data system corresponds to a structure, a unit of data, a data subsystem, a relationship between units or subsystems, a process, or a spatial form.