System and method for temporal data mining
First Claim
1. A method for signal characterization comprising an integrated search algorithm that cooperatively optimizes data mining sub-tasks, the integrated search algorithm including a machine learning model, the method comprising:
- processing the data for data embedding;
data embedding the processed data for searching for patterns;
extracting time and frequency patterns to provide training samples; and
training the machine learning model to represent learned patterns for signal characterization according to the training samples.
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Abstract
A system, method, and apparatus for signal characterization, estimation, and prediction comprising an integrated search algorithm that cooperatively optimizes several data mining sub-tasks, the integrated search algorithm including a machine learning model, and the method comprising processing the data for data embedding, data embedding the processed data for searching for patterns, extracting time and frequency patterns, and training the model to represent learned patterns for signal characterization, estimation, and prediction.
157 Citations
20 Claims
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1. A method for signal characterization comprising an integrated search algorithm that cooperatively optimizes data mining sub-tasks, the integrated search algorithm including a machine learning model, the method comprising:
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processing the data for data embedding;
data embedding the processed data for searching for patterns;
extracting time and frequency patterns to provide training samples; and
training the machine learning model to represent learned patterns for signal characterization according to the training samples. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system for signal characterization, comprising:
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a processor adapted to execute instructions of a software module;
an instruction module comprising an integrated search algorithm that cooperatively optimizes data mining sub-tasks, the integrated search algorithm including a machine learning model;
a processing module for processing the data for data embedding;
an embedding module for data embedding the processed data for searching for time and frequency patterns;
an extraction module for extracting time and frequency patterns to provide training samples; and
a training module for training the machine learning model to represent learned patterns according to the training samples. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17)
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18. A method for temporal data mining utilizing a processor adapted to execute instructions of a software module and a database comprising time series data;
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executing genetic algorithm instructions, comprising;
a binning and classifying module;
a data embedding module;
a temporal pattern extraction module; and
a neural network training module;
processing the time series data by the genetic algorithm instructions; and
generating prediction output. - View Dependent Claims (19, 20)
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Specification