Abstract: An optimization formulation for designing signal-dependent kernels that are based on radially Gaussian functions is presented.

In this paper, a new procedure that is based on optimization criteria and radially-Gaussian functions is intro- duced for signal-dependent kernel design.

In this paper, we propose a signal-dependent kernel that changes shape for each signal to offer improved time-frequency representation for a large class of ...

An optimization formulation for designing signal-dependent kernels that are based on radially Gaussian functions is presented.

In this paper, we propose a signal-dependent kernel that changes shape for each signal to offer improved time-frequency representation for a large class of ...

An optimization formulation for designing signal-dependent kernels that are based on radially Gaussian functions is presented.

In this paper, I propose an adaptive RGK estimation method to estimate the RGK directly from the ambiguity function (AF) in polar coordinates, without solving ...

Dive into the research topics of 'A radially-Gaussian, signal-dependent time-frequency representation'. Together they form a unique fingerprint. Sort by; Weight ...

Abstract. We propose a method for tuning time-frequency distributions with radially Gaussian kernel within a classification framework.

In this paper, we propose a method for tuning time-frequency distributions with radially Gaussian kernel within a classi- fication framework.