D

Digital Signal Processing

License: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/

The effective algorithm for constant state detection in time series.

Andrei Keino

February 14, 2025

Abstract The article introduces simple and effective algorithm for constant state detection in time series. The algorithm, based on sliding window of variable length, searches a sections of time series which have length more or equal than some given minimal length and have difference between maximal and minimal value in the section less or equal than some given value. It is shown that the computational complexity of aforementioned algorithm is O(N log N), where N is the length of time series.

The aim of this project is to provide an exploratory analysis of Domain Adaptation (DA) techniques in the context of PHM for Bearings fault prognosis, focusing on Health Index (HI) estimation and Remaining Useful Life (RUL) prediction. The adopted dataset is the PRONOSTIA/FEMTO-ST bearings dataset.

Fundamental digital signal processing operations implemented and tested in Rust.

Implementing hands free or touch free musical instruments