IWAVE -- An Adaptive Filter Approach to Phase Lock and the Dynamic Characterisation of Pseudo-Harmonic Waves

TL;DR

IWAVE is an innovative adaptive filtering method designed for real-time dynamic characterization of pseudo-harmonic waves in noisy environments, outperforming traditional techniques in accuracy and versatility.

Contribution

The paper introduces IWAVE, a novel adaptive filter algorithm that improves the detection and analysis of oscillating signals with varying frequency and amplitude in noisy data.

Findings

IWAVE effectively characterizes waves in simulated data.

IWAVE performs well on real-world noisy data.

The method offers advantages over conventional techniques.

Abstract

We present a novel adaptive filtering approach to the dynamic characterisation of waves of varying frequency and amplitude embedded in arbitrary noise backgrounds. This method, known as IWAVE, possesses critical advantages over conventional techniques making it a useful new tool in the dynamic characterisation of a wide range of data containing embedded oscillating signals. After a review of existing techniques, we present the IWAVE algorithm, derive its key characteristics, and provide tests of its performance using simulated and real world data.