GitHub

10-2--sklearn--thresholding-binary-feature-variance--VarianceThreshold.py

# Observations of feature 0: (0, 0, 0, 0, 1) -> 80% of class 0 and 20% of class 1 # Observations of feature 1: (1, 1, 1, 1, 0) -> 20% of class 0 and 80% of class 1 ...
GitHub

10-1--sklearn--thresholding-numerical-feature-variance--VarianceThreshold.py

Filter out a set of numerical features with low variance (i.e., likely containing little information). Use Variance thresholding (VT). Idea: features with low variance are likely less interesting (and ...
IEEE

Channel Estimation With Iterative Hard Thresholding in mMTC Communications

Abstract: In the context of Internet of Things (IoT) applications, the field of massive Machine-Type Communications (mMTC) has experienced rapid development, but still faces specific challenges such ...
IEEE

Robust R-Peak Detection in Terahertz Pulse Signals Using Adaptive Thresholding

Abstract: We propose a robust algorithm for detecting R-peaks in terahertz-wave plethysmography (TPG) signals to enable accurate pulse rate estimation. Unlike prior methods based on frequency domain ...