Oracle International Corporation

Ruixian Liu

Guang Chao Wang

Kenny C Gross

Keyang Ru

Denesh Kumar Krishnan Rajaram

Systems, methods, and other embodiments associated with automatic configuration of a circular buffer for ingesting a stream and generating ML estimates in real-time are described. In one embodiment, an example method includes loading a stream of multivariate time series observations into a circular buffer at a real-time pace of input from a target asset. The circular buffer is configured with a buffer configuration that specifies buffer length and choice of arrangement as a single-buffer or dual-buffer. The method then adjusts the buffer configuration until generation of machine learning estimates of the multivariate time series observations that are in the circular buffer satisfies a threshold test for generation at the real-time pace. And, at the real time pace, the method loads additional multivariate time series observations into the circular buffer that is in the adjusted configuration and generates additional machine learning estimates of the additional multivariate time series observations.

Configurable circular buffer for streaming multivariate ML estimation

Systems, methods, and other embodiments associated with frequency-domain resampling of time series are described. An example method includes generating a power spectrum for a first time series signal that is sampled inconsistently with a target sampling rate. Prominent frequencies are selected from the power spectrum. Sets of first phase factors that map the prominent frequencies to a frequency domain at first time points are generated. Coefficients are identified that relate the sets of first phase factors to values of the first time series signal at the first time points. Sets of second phase factors that map the prominent frequencies to a frequency domain at second time points are generated. A second time series signal that is resampled at the target sampling rate is generated by generating new values at the second time points from the coefficients and sets of second phase factors.

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Ruixian Liu