COMBINED-MODEL DATA COMPRESSION
First Claim
1. A method, performed by a computing device having a processor and memory, for compressing data, the method comprising:
- receiving data comprising indications of a signal;
deriving, using at least a first prediction model and a second prediction model, a combined prediction model by operating the first prediction model on a first subset of the data and operating the second prediction model on a second subset of the data, wherein the first subset of data contains data also in the second subset of the data;
predicting a future value for the signal using the combined prediction model;
applying a function configured to determine a distinction between the predicted future value for the signal and an actual value for the signal; and
compressing the data based at least in part on the determined distinction.
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Abstract
Data compression technology (“the technology”) is disclosed that can employ two or more prediction models contemporaneously. The technology receives data from one or more sources; shifts or re-sample one of more corresponding signals; creates a prediction model of uncompressed samples using at least two different individual or composite models; selects a subset of the models for prediction of samples; determines an order in which signals will be compressed; formulates a combined predictions model using the selected subset of models; predicts a future value for the data using the combined compression model; defines a function that has as parameters at least the predicted future values for the data and actual values; selects a compression method for the values of the function; and compresses the data using at least the predicted value of the function.
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Citations
24 Claims
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1. A method, performed by a computing device having a processor and memory, for compressing data, the method comprising:
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receiving data comprising indications of a signal; deriving, using at least a first prediction model and a second prediction model, a combined prediction model by operating the first prediction model on a first subset of the data and operating the second prediction model on a second subset of the data, wherein the first subset of data contains data also in the second subset of the data; predicting a future value for the signal using the combined prediction model; applying a function configured to determine a distinction between the predicted future value for the signal and an actual value for the signal; and compressing the data based at least in part on the determined distinction. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer-readable storage medium storing instructions that, when executed by a computing device, cause the computing device to perform operations for compressing data, the operations comprising:
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shifting or re-sampling one or more signals corresponding to data received from one or more sources; formulating a combined prediction model based at least in part on two different models, each model operating on at least two subsets of the received data, wherein at least one subset of the at least two subsets contains data in at least one other subset of the at least two subsets; predicting a future value for the received data using the combined prediction model; applying a function that has as parameters at least the predicted future value for the received data and an actual value for the received data; and compressing the received data using at least a value calculated by the function. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A system, including one or more processors and memory, for compressing data, the system comprising:
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means for receiving data comprising one or more signals; means for creating a prediction model using at least two different models; means for selecting a subset of the models for sample prediction; means for determining an order in which the selected subset of models will be applied to the data; means for formulating future values at least in part by applying the selected subset of models in the determined order; means for applying a function that has as parameters at least (1) the predicted future values for the data and (2) measured values corresponding to the predicted future values for the data; and means for compressing the data based at least in part on values calculated by the function. - View Dependent Claims (22, 23, 24)
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Specification