Systems and methods for analyzing sensor data using incremental autoregression techniques
Abstract:
This disclosure relates to systems and methods for analyzing sensor data using incremental autoregression techniques for generating a vector of autoregression coefficients is provided. The system processes a time series data to obtain blocks of observation values, reads the observation values, updates pre-stored convolution values with the observation values, updates a partial sum by adding each observation value to the partial sum, increments a count each time an observation value is read, repeats the steps of updates and increments until a last observation value from a last block is read to obtain an updated set of convolution values, partial sum, and count. The system further computes a first matrix and a second matrix using the updated set of convolutions values, or summation of observation values computed from the updated partial sum, or the updated count, and generates a vector of autoregression coefficients based on the first and the second matrix.
Information query
Patent Agency Ranking
0/0