Fundamental component enhancement via adaptive nonlinear activation functions

12/03/2021
by   Stefan Steinerberger, et al.
Duke University
University of Washington
0

In many real world oscillatory signals, the fundamental component of a signal f(t) might be weak or does not exist. This makes it difficult to estimate the instantaneous frequency of the signal. Traditionally, researchers apply the rectification trick, working with |f(t)| or (f(t)) instead, to enhance the fundamental component. This raises an interesting question: what type of nonlinear function g:ℝ→ℝ has the property that g(f(t)) has a more pronounced fundamental frequency? g(t) = |t| and g(t) = (t) seem to work well in practice; we propose a variant of g(t) = 1/(1-|t|) and provide a theoretical guarantee. Several simulated signals and real signals are analyzed to demonstrate the performance of the proposed solution.

READ FULL TEXT
05/16/2023

Hardware Realization of Nonlinear Activation Functions for NN-based Optical Equalizers

To reduce the complexity of the hardware implementation of neural networ...
05/31/2021

Node-Variant Graph Filters in Graph Neural Networks

Graph neural networks (GNNs) have been successfully employed in a myriad...
02/01/2019

Multi-layered Cepstrum for Instantaneous Frequency Estimation

We propose the multi-layered cepstrum (MLC) method to estimate multiple ...
03/24/2022

Steganalysis of Image with Adaptively Parametric Activation

Steganalysis as a method to detect whether image contains se-cret messag...

Please sign up or login with your details

Forgot password? Click here to reset