Efficiency improvements to an auditory-inspired synchrony capture filterbank

This paper extends prior work on an auditory inspired adaptive synchrony capture filterbank (SCFB) architecture for acoustic frequency tracking. The earlier SCFB architecture used a weighted sum of frequency discriminator loop (FDL) and a phased locked loop (PLL) to track frequency components precisely. The key improvements in this paper are the introduction of adaptive FDL and PLL weights and the incorporation of a place theory-based mechanism to preferentially activate fewer filters, resulting in enhanced biomimicry and computational efficiency. The effectiveness of these improvements is demonstrated using synthetic time-varying signals, simultaneously highlighting the algorithm's robust denoising capability under challenging noise conditions.