With the development of communication technology, the electronic signals of communication
countermeasures become more and more complex. Facing the increasingly complicated …

Most of the existing intelligent algorithms for identifying real and false targets are based on
supervised learning and perform poorly under a low signal-to-noise ratio. Considering the …

Most of the real-world signals in nature are non-stationary, ie, their statistics are time variant.
Extracting the time-varying frequency characteristics of a signal is very important in …

In high-density radio frequency (RF) signal environments, receivers usually acquire signals
from multiple sources. These RF signals may be co-channel and co-duration, which cause …

Most existing classification methods cannot work in low signal-to-noise ratio (SNR)
environments. This limitation motivates the signal filtering before the classification process …

Extensive research is carried out in classifying non stationary signals as normal or
abnormal. Considerable research is carried out in applying various transforms namely …

New algorithms for the analysis of signals with time-varying instantaneous frequency. Page 1
This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological …

In this paper, an evaluation of time-frequency analysis techniques is presented as applied to
the detection of finite duration communication signals. This class of signals includes both …

In order to acquire outer cross term free time frequency distribution of multi-component
nonstationary signal, filter bank technique was used to decompose the signal being …

The concept of instantaneous frequency (IF) and its traditional construct method--analytic
method are introduced in this paper. Then by means of joint time-frequency analysis, the …