In this paper, we design an attractivealgorithm aiming to classify moving targets includinghuman, animal, vehicle and drone, at groundsurveillance radar systems. The non-stationary reflectedsignal of the targets is represented with a novelmathematical framework based on behavior of thesignal components in reality. We further propose usingthe generalized linear chirp transform for the analysisst...

With the wide application of spectral and algebraic theory in discrete signal processing techniques field graph processing, an increasing number methods have been proposed, such as Fourier transform, wavelet transform windowed transform. In this paper, we propose design definition linear canonical on graphs (GLCT), which is extension (DLCT), just (GFT) (DFT). First, based centrality scalability...

The chirplet transform is the generalization form of fast Fourier Transform, short-time Fourier transform, and wavelet transform. It has the most flexible time frequency window and successfully used in practices. However, the chirplet transform has not inherent inverse transform, and can not overcome the signal reconstructing problem. In this paper, we proposed the improved 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...

A hypersurface D in C n is a linear free divisor if the module of logarithmic vector fields along D has a basis of global linear vector fields. It is then defined by a homogeneous polynomial of degree n and its complement is an open orbit of an algebraic subgroup G D of Gln(C) whose Lie algebra g D can be identified with that of linear logarithmic vector fields along D. We classify all linear f...

Most speech processing models begin with feature extraction and then pass the vector to primary model. The solution's performance mainly depends on quality of representation model architecture. Much research focuses designing robust deep network architecture ignoring representation's important role during neural era. This work aims exploit a new approach design signal in time-frequency domain v...

Using the Wigner distribution, we derive and analyze a matrix formulation for the chirplet transform, a signal analysis tool that generalizes the wavelet and short-time Fourier transforms. The formulation expresses the translations, scalings, and shears of the chirplet transform in terms of affine matrix transformations on the time-frequency plane. Our approach leads naturally to several new si...

A complex hypersurface D in Cn is a linear free divisor (LFD) if its module of logarithmic vector elds has a global basis of linear vector elds. We classify all LFDs for n at most 4. By analogy with Grothendieck's comparison theorem, we say that the global logarithmic comparison theorem (GLCT) holds for D if the complex of global logarithmic di erential forms computes the complex cohomology of ...