view matlab/bmm/carfac/MultiScaleSmooth.m @ 593:40934f897a56

Fixed certain minor documentation bugs.
Added the CAR::designFilters and CAR::stageG methods. These methods design the CAR.coeff coefficients. They have been compared to be the same as the matlab coefficients.
An Ear is now contructed with a specific FS or, it uses the default.
Added the PsychoAcoustics class to do ERB and Hz conversions.
Added the EarTest.C main which allows the construction of an Ear class for testing.

% Copyright 2012 Google Inc. All Rights Reserved.
% Author: Richard F. Lyon
%
% This Matlab file is part of an implementation of Lyon's cochlear model:
% "Cascade of Asymmetric Resonators with Fast-Acting Compression"
% to supplement Lyon's upcoming book "Human and Machine Hearing"
%
% Licensed under the Apache License, Version 2.0 (the "License");
% you may not use this file except in compliance with the License.
% You may obtain a copy of the License at
%
%     http://www.apache.org/licenses/LICENSE-2.0
%
% Unless required by applicable law or agreed to in writing, software
% distributed under the License is distributed on an "AS IS" BASIS,
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
% See the License for the specific language governing permissions and
% limitations under the License.

function MultiScaleSmooth(waves, n_scales)
% function MultiScaleSmooth(waves, n_scales)
%
% Let's take columns as waveforms, and smooth them to different scales;
% these inputs can be carfac NAPs, for example, and the peaks of the
% smoothed versions can be used as trigger events, even tracking back
% to less-smoothed versions.
% And we'll deciamte 2:1 at every other smoothing.
%
% Until we decide what we want, we'll just plot things, one plot per scale.

fig_offset1 = 10;

if nargin < 2
  n_scales = 20;
end

smoothed = waves;

for scale_no = 1:n_scales

  if mod(scale_no, 2) == 1
    newsmoothed = filter([1, 1]/2, 1, smoothed);
    diffsmoothed = max(0, smoothed - newsmoothed);
    smoothed = newsmoothed;
  else
    newsmoothed = filter([1, 2, 1]/4, 1, smoothed);
    diffsmoothed = max(0, smoothed - newsmoothed);
    smoothed = newsmoothed(1:2:end, :);
  end

  figure(scale_no + fig_offset1)
  imagesc(squeeze(smoothed(:,:,1))')

  drawnow
  pause(1)

end