Time-frequency analysis and Harmonic Gaussian Functions
📝 Original Info
- Title: Time-frequency analysis and Harmonic Gaussian Functions
- ArXiv ID: 1303.1909
- Date: 2015-04-29
- Authors: Researchers from original ArXiv paper
📝 Abstract
A method for time-frequency analysis is given. The approach utilizes properties of Gaussian distribution, properties of Hermite polynomials and Fourier analysis. We begin by the definitions of a set of functions called harmonic Gaussian functions. Then these functions are used to define a set of transformations,noted T_n, which associate to a function {\psi},of the time variable t, a set of functions {\Psi}_n which depend on time, frequency and frequency (or time) standard deviation. Some properties of the transformations T_n and the functions {\Psi}_n are given. It is proved in particular that the square of the modulus of each function {\Psi}_n can be interpreted as a representation of the energy distribution of the signal, represented by the function {\psi}, in the time-frequency plane for a given value of the frequency (or time) standard deviation. It is also shown that the function {\psi}, can be recovered from the functions{\Psi}_n.💡 Deep Analysis
Deep Dive into Time-frequency analysis and Harmonic Gaussian Functions.A method for time-frequency analysis is given. The approach utilizes properties of Gaussian distribution, properties of Hermite polynomials and Fourier analysis. We begin by the definitions of a set of functions called harmonic Gaussian functions. Then these functions are used to define a set of transformations,noted T_n, which associate to a function {\psi},of the time variable t, a set of functions {\Psi}_n which depend on time, frequency and frequency (or time) standard deviation. Some properties of the transformations T_n and the functions {\Psi}_n are given. It is proved in particular that the square of the modulus of each function {\Psi}_n can be interpreted as a representation of the energy distribution of the signal, represented by the function {\psi}, in the time-frequency plane for a given value of the frequency (or time) standard deviation. It is also shown that the function {\psi}, can be recovered from the functions{\Psi}_n.