view matlab/bmm/carfac/CARFAC_Run_Linear.m @ 611:0fbaf443ec82

Carfac C++ revision 3, indluding more style improvements. The output structs are now classes again, and have separate storage methods for each output structure along with flags in the Run and RunSegment methods to allow for only storing NAPs if desired.

% Copyright 2012, Google, Inc.
% 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 [naps, CF] = CARFAC_Run_Linear(CF, input_waves, relative_undamping)
% function [naps, CF] = CARFAC_Run_Linear(CF, input_waves, relative_undamping)
%
% This function runs the CARFAC; that is, filters a 1 or more channel
% sound input to make one or more neural activity patterns (naps);
% however, unlike CARFAC_Run, it forces it to be linear, and gives a
% linear (not detected) output.

% only saving one of these, really:
velocity_scale = CF.ears(1).CAR_coeffs.velocity_scale;
for ear = 1:CF.n_ears
  % make it effectively linear for now
  CF.ears(ear).CAR_coeffs.velocity_scale = 0;
end

[n_samp, n_ears] = size(input_waves);
n_ch = CF.n_ch;

if nargin < 3
  relative_undamping = 1;  % default to min-damping condition
end

if n_ears ~= CF.n_ears
  error('bad number of input_waves channels passed to CARFAC_Run')
end

for ear = 1:CF.n_ears
  coeffs = CF.ears(ear).CAR_coeffs;
  % Set the state of damping, and prevent interpolation from there:
  CF.ears(ear).CAR_state.zB_memory(:) = coeffs.zr_coeffs .* relative_undamping;  % interpolator state
  CF.ears(ear).CAR_state.dzB_memory(:) = 0;  % interpolator slope
  CF.ears(ear).CAR_state.g_memory = CARFAC_Stage_g(coeffs, relative_undamping);
  CF.ears(ear).CAR_state.dg_memory(:) = 0;  % interpolator slope
end

naps = zeros(n_samp, n_ch, n_ears);

for k = 1:n_samp
  % at each time step, possibly handle multiple channels
  for ear = 1:n_ears
    [filters_out, CF.ears(ear).CAR_state] = CARFAC_CAR_Step( ...
      input_waves(k, ear), CF.ears(ear).CAR_coeffs, CF.ears(ear).CAR_state);
    naps(k, :, ear) = filters_out;  % linear
  end
  % skip IHC and AGC updates
end

for ear = 1:CF.n_ears
  CF.ears(ear).CAR_coeffs.velocity_scale = velocity_scale;
end