Mercurial > hg > aimc
view trunk/matlab/bmm/carfac/CARFAC_Run_Linear.m @ 668:933cf18d9a59
Fourth revision of Alex Brandmeyer's C++ implementation. Fixed more style issues, changed AGC structures to vectors, replaced FloatArray2d with vector<FloatArray>, implemented first tests using GTest to verify coefficients and monaural output against Matlab values (stored in aimc/carfac/test_data/). To run tests, change the path stored in carfac_test.h in TEST_SRC_DIR. Added CARFAC_GenerateTestData to the Matlab branch, fixed stage indexing in CARFAC_Cross_Couple.m to reflect changes in AGCCoeffs and AGCState structs.
author | alexbrandmeyer |
---|---|
date | Wed, 22 May 2013 21:30:02 +0000 |
parents | 3e2e0ab4f708 |
children |
line wrap: on
line source
% 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