Modeling auditory cortical processing as an adaptive chirplet transform

A fast refinement for adaptive Gaussian chirplet decomposition

The chirp function is one of the most fundamental functions in nature. Many natural events, for example, most signals encountered in seismology and the signals in radar systems, can be modeled as the superposition of short-lived chirp functions. Hence, the chirp-based signal representation, such as the Gaussian chirplet decomposition, has been an active research area in the field of signal proc...

Adaptive "chirplet" transform: an adaptive generalization of the wavelet transform

Time-frequency Perspectives: the “chirplet” Transform

We have developed a new expansion’ we call the “chirplet transform”. It has been successfully applied to a wide variety of signal processing applications including radar[l] and image processing. There has been a recent debate as to the relative merits of an affine-in-time (wavelet) transform and the classical Short Time Fourier Transform (STFT), for the analysis of non-stationary phenomena. Chi...

Fast Chirplet Transform feeding CNN, application to orca and bird bioacoustics

Advanced soundscape analysis or machine listening are requiring efficient time frequency decompositions. The recent scattering theory is offering a robust hierarchical convolutional decomposition, nevertheless its kernels need to be fixed. The CNN can be seen as the optimal kernel decomposition, nevertheless it requires large amount of training data. This paper aims to show that Chirplet kernel...

Manoeuvring target detection in over-the-horizon radar using adaptive clutter rejection and adaptive chirplet transform

In over-the-horizon radar (OTHR) systems, the signal-to-clutter ratio (SCR) used for moving target detection is very low. For slowly moving targets such as ships, the SCR is typically from 250 dB to 260 dB and their Doppler frequencies are close to that of the clutter. For manoeuvring targets, such as aircraft and missiles, the Doppler frequencies are time-varying when a long integration time i...