ASTF: Visual Abstractions of Time-Varying Patterns in Radio Signals

09/30/2022
by   Ying Zhao, et al.
0

A time-frequency diagram is a commonly used visualization for observing the time-frequency distribution of radio signals and analyzing their time-varying patterns of communication states in radio monitoring and management. While it excels when performing short-term signal analyses, it becomes inadaptable for long-term signal analyses because it cannot adequately depict signal time-varying patterns in a large time span on a space-limited screen. This research thus presents an abstract signal time-frequency (ASTF) diagram to address this problem. In the diagram design, a visual abstraction method is proposed to visually encode signal communication state changes in time slices. A time segmentation algorithm is proposed to divide a large time span into time slices.Three new quantified metrics and a loss function are defined to ensure the preservation of important time-varying information in the time segmentation. An algorithm performance experiment and a user study are conducted to evaluate the effectiveness of the diagram for long-term signal analyses.

READ FULL TEXT

page 1

page 2

page 6

research
12/29/2018

Adaptive Short-time Fourier Transform and Synchrosqueezing Transform for Non-stationary Signal Separation

The synchrosqueezing transform, a kind of reassignment method, aims to s...
research
08/25/2023

TFDNet: Time-Frequency Enhanced Decomposed Network for Long-term Time Series Forecasting

Long-term time series forecasting is a vital task and has a wide range o...
research
05/13/2021

Dyadic aggregated autoregressive (DASAR) model for time-frequency representation of biomedical signals

This paper introduces a new time-frequency representation method for bio...
research
02/03/2021

Mortality Forecasting using Factor Models: Time-varying or Time-invariant Factor Loadings?

Many existing mortality models follow the framework of classical factor ...
research
07/20/2019

Efficient Bayesian PARCOR Approaches for Dynamic Modeling of Multivariate Time Series

A Bayesian lattice filtering and smoothing approach is proposed for fast...
research
03/15/2018

On the Underspread/Overspread Classification of Random Processes

We study the impact of the recently introduced underspread/overspread cl...
research
09/13/2023

Ridge detection for nonstationary multicomponent signals with time-varying wave-shape functions and its applications

We introduce a novel ridge detection algorithm for time-frequency (TF) a...

Please sign up or login with your details

Forgot password? Click here to reset