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📄 tfrspaw.tex

📁 时频分析的工具包
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% This is part of the TFTB Reference Manual.% Copyright (C) 1996 CNRS (France) and Rice University (US).% See the file refguide.tex for copying conditions.\markright{tfrspaw}\hspace*{-1.6cm}{\Large \bf tfrspaw}\vspace*{-.4cm}\hspace*{-1.6cm}\rule[0in]{16.5cm}{.02cm}\vspace*{.2cm}{\bf \large \fontfamily{cmss}\selectfont Purpose}\\\hspace*{1.5cm}\begin{minipage}[t]{13.5cm}Smoothed pseudo affine Wigner time-frequency distributions.\end{minipage}\vspace*{.5cm}{\bf \large \fontfamily{cmss}\selectfont Synopsis}\\\hspace*{1.5cm}\begin{minipage}[t]{13.5cm}\begin{verbatim}[tfr,t,f] = tfrspaw(x)[tfr,t,f] = tfrspaw(x,t)[tfr,t,f] = tfrspaw(x,t,k)[tfr,t,f] = tfrspaw(x,t,k,nh0)[tfr,t,f] = tfrspaw(x,t,k,nh0,ng0)[tfr,t,f] = tfrspaw(x,t,k,nh0,ng0,fmin,fmax)[tfr,t,f] = tfrspaw(x,t,k,nh0,ng0,fmin,fmax,N)[tfr,t,f] = tfrspaw(x,t,k,nh0,ng0,fmin,fmax,N,trace)\end{verbatim}\end{minipage}\vspace*{.5cm}{\bf \large \fontfamily{cmss}\selectfont Description}\\\hspace*{1.5cm}\begin{minipage}[t]{13.5cm}        {\ty tfrspaw} generates the auto- or cross- smoothed pseudo affine        Wigner distributions. Its general expression writes\begin{eqnarray*}\tilde{P}_x^k(t,\nu)=\int_{-\infty}^{+\infty}\dfrac{\mu_k(u)}{\sqrt{\lambda_k(u)\lambda_k(-u)}}\  T_x(t,\lambda_k(u)\nu;\psi)\ T_x^*(t,\lambda_k(-u)\nu;\psi)\ du,\end{eqnarray*}where $T_x(t,\nu;\psi)$ is the continuous wavelet transform,\[\psi(t)=(\pi t_0^2)^{-1/4}\exp\left[-\frac{1}{2}(t/t_0)^2 +j2\pi\nu_0t\right]\] is the Morlet wavelet, and$\lambda_k(u,k)=\left(\dfrac{k(e^{-u}-1)}{e^{-ku}-1}\right)^{\frac{1}{k-1}}.$\\\hspace*{-.5cm}\begin{tabular*}{14cm}{p{1.5cm} p{9.5cm} c}Name & Description & Default\\\hline        {\ty x} & signal (in time) to be analyzed. If {\ty x=[x1 x2]}, {\ty tfrspaw}           computes the cross-smoothed pseudo affine Wigner distribution.                                                {\ty (Nx=length(X))}\\        {\ty t} & time instant(s) on which the {\ty tfr} is evaluated & {\ty (1:Nx)}\\        {\ty k} & label of the distribution          & 0\\      & \hspace*{.2cm} {\ty k=-1  :} smoothed pseudo active Unterberger  \\      & \hspace*{.2cm} {\ty k=0   :} smoothed pseudo Bertrand \\      & \hspace*{.2cm} {\ty k=1/2 :} smoothed pseudo D-Flandrin \\      & \hspace*{.2cm} {\ty k=2   :} affine smoothed pseudo Wigner-Ville\\\hline\end{tabular*}\end{minipage} %\newpage\hspace*{1.5cm}\begin{minipage}[t]{13.5cm}\hspace*{-.5cm}\begin{tabular*}{14cm}{p{1.5cm} p{9cm} c}Name & Description & Default value\\\hline        {\ty nh0} & half length of the analyzing wavelet at coarsest scale.             A Morlet wavelet is used. {\ty nh0} controls the frequency            smoothing of the smoothed pseudo affine Wigner distribution                                                & {\ty sqrt(Nx)}\\        {\ty ng0} & half length of the time smoothing window.         {\ty ng0=0} corresponds to the pseudo affine Wigner distribution                                                  & {\ty 0}\\        {\ty fmin, fmax} & respectively lower and upper frequency bounds of            the analyzed signal. These parameters fix the equivalent            frequency bandwidth (expressed in Hz). When unspecified, you           have to enter them at the command line from the plot of the           spectrum. {\ty fmin} and {\ty fmax} must be $>${\ty 0} and $\leq${\ty 0.5}\\        {\ty N} & number of analyzed voices & auto\footnote{This value,	determined from {\ty fmin} and {\ty fmax}, is the 	next-power-of-two of the minimum value checking the non-overlapping	condition in the fast Mellin transform.}\\        {\ty trace} & if nonzero, the progression of the algorithm is shown                                                & {\ty 0}\\     \hline {\ty tfr} & time-frequency matrix containing the coefficients of the           decomposition (abscissa correspond to uniformly sampled time,           and ordinates correspond to a geometrically sampled           frequency). First row of {\ty tfr} corresponds to the lowest            frequency\\        {\ty f} & vector of normalized frequencies (geometrically sampled            from {\ty fmin} to {\ty fmax})\\ \hline\end{tabular*}\vspace*{.1cm}When called without output arguments, {\ty tfrspaw} runs {\ty tfrqview}.\end{minipage}\vspace*{.5cm}{\bf \large \fontfamily{cmss}\selectfont Example}\begin{verbatim}         sig=altes(64,0.1,0.45);          tfrspaw(sig);\end{verbatim}\vspace*{.4cm}{\bf \large \fontfamily{cmss}\selectfont See Also}\\\hspace*{1.5cm}\begin{minipage}[t]{13.5cm}all the {\ty tfr*} functions.\end{minipage}\vspace*{.4cm}{\bf \large \fontfamily{cmss}\selectfont Reference}\\\hspace*{1.5cm}\begin{minipage}[t]{13.5cm}[1] P. Gon鏰lv鑣, R. Baraniuk ``Pseudo Affine Wigner Distributions andKernel Formulation'' Submitted to IEEE Transactions on Signal Processing,1996. \end{minipage}

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