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📄 rgk.guide

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%    RGK.m                  Version 1.0                   4 February 1995%    The following information is included in the Matlab function rgk.m :%----------------------------------------------------------------------------%% SIGNAL-DEPENDENT TIME-FREQUENCY ANALYSIS USING A RADIAL GAUSSIAN KERNEL    %%----------------------------------------------------------------------------%%% This Matlab function implements the ``Optimal Radially Gaussian Kernel% Time-Frequency Representation.''  For details, please consult either% the paper%%    R. G. Baraniuk and D. L. Jones, ``Signal-Dependent Time-Frequency%    Analysis Using a Radially Gaussian Kernel,'' Signal Processing, %    Vol. 32, No. 3, pp. 263-284, June 1993.%% or the thesis%%    R. G. Baraniuk, ``Shear Madness: Signal-Dependent and Metaplectic %    Time-Frequency Representations,'' Ph.D. Thesis, Department of%    Electrical and Computer Engineering, University of Illinois at%    Urbana-Champaign, August 1992.  Also Coordinated Science Laboratory%    Technical Report No. UILU-ENG-92-2226, 1992.  See Chapter 6 and%    Appendices B and G.%% Equation numbers in the comments below refer to the paper unless% otherwise noted.  We have tried to keep as close as possible to the% notation of these documents.%%% FLOW OF THE ALGORITHM:%% Step 1:   Compute the rectangularly sampled ambiguity function (AF)%           of the signal%%           *** Uses the separate function AMBNB ***%                (included in this distribution)%% Step 2:   Interpolate the AF to polar coordinates%% Step 3:   Solve for the optimal kernel spread vector using the%           so-called "step-project" algorithm [Eqs. (40)-(42)]%% Step 4:   Compute the optimal kernel in polar coordinates%% Step 5:   Interpolate the optimal kernel to rectangular coordinates%% Step 6:   Inverse FFT the optimal-kernel x AF product to get the%           optimal time-frequency representation%%% QUESTIONS?  COMMENTS?  Drop us a line:%%             Paulo Goncalves    gpaulo@rice.edu%             Richard Baraniuk   richb@rice.edu%                                http://www-dsp.rice.edu%%----------------------------------------------------------------------------%% Help information available in Matlab:%RGK  Optimal radially Gaussian kernel time-frequency representation%%  Useage:    [tfr,Phi,sigma,its] = rgk(s,alpha)%%  Input:   - s     : column or row vector containing the signal to be%                     analyzed%           - alpha : normalized volume of the optimal kernel%                     reasonable values:  1 < alpha < 5%                     alpha = 1 => optimal kernel has same volume as a%                     spectrogram kernel%%  Output:  - tfr   : optimal radially Gaussian time-frequency representation%           - Phi   : optimal radially Gaussian kernel%           - sigma : spread function parametrized by the radial angle in the %                     ambiguity domain%           - its   : number of iterations of the step-projection algorithm%                     to converge to a (local) maximum%%  Example:   Two parallel linear chirps%             t = (0:127);%             s1 = hamming(128)' .* cos(0.2*t + 0.008*t.^2);%             s2 = hamming(128)' .* cos(0.6*t + 0.008*t.^2);%             s = s1 + s2;%             tfr = rgk(s,2);%             contour(tfr); xlabel('time'); ylabel('frequency')%%  See also:  AMBNB%  Copyright information:%----------------------------------------------------------------------------%%File Name: rgk.m%Last Modification Date: 1/26/96	18:30:22%Current Version: rgk.m	1.2%File Creation Date: Sun Jan 21 16:36:09 1996%Author: Paulo Goncalves  <gpaulo@ece.rice.edu>%Extra Verbiage: Richard Baraniuk <richb@rice.edu>%%Copyright: All software, documentation, and related files in this distribution%           are Copyright (c) 1996 Rice University%%Permission is granted for use and non-profit distribution providing that this%notice be clearly maintained. The right to distribute any portion for profit%or as part of any commercial product is specifically reserved for the author.%%Change History:%%----------------------------------------------------------------------------%

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