function [U_exc] = generateShapedNoise(args) % generateShapedNoise - Generate a Shaped Noise excitation signal % % Syntax: [U_exc] = generateShapedNoise(args) % % Inputs: % - args - Optinal arguments: % - Ts - Sampling Time - [s] % - V_mean - Mean value of the excitation voltage - [V] % - V_exc - Excitation Amplitude, could be numeric or TF - [V rms] % - t_start - Time at which the noise begins - [s] % - exc_duration - Duration of the noise - [s] % - smooth_ends - 'true' or 'false': smooth transition between 0 and V_mean - [-] arguments args.Ts (1,1) double {mustBeNumeric, mustBePositive} = 1e-4 args.V_mean (1,1) double {mustBeNumeric} = 0 args.V_exc = 1 args.t_start (1,1) double {mustBeNumeric, mustBePositive} = 5 args.exc_duration (1,1) double {mustBeNumeric, mustBePositive} = 10 args.smooth_ends logical {mustBeNumericOrLogical} = true end t_noise = 0:args.Ts:args.exc_duration; if isnumeric(args.V_exc) V_noise = args.V_mean + args.V_exc*sqrt(1/args.Ts/2)*randn(length(t_noise), 1)'; elseif isct(args.V_exc) V_noise = args.V_mean + lsim(args.V_exc, sqrt(1/args.Ts/2)*randn(length(t_noise), 1), t_noise)'; end t_smooth_start = args.Ts:args.Ts:args.t_start; V_smooth_start = zeros(size(t_smooth_start)); V_smooth_end = zeros(size(t_smooth_start)); if args.smooth_ends Vd_max = args.V_mean/(0.7*args.t_start); V_d = zeros(size(t_smooth_start)); V_d(t_smooth_start < 0.2*args.t_start) = t_smooth_start(t_smooth_start < 0.2*args.t_start)*Vd_max/(0.2*args.t_start); V_d(t_smooth_start > 0.2*args.t_start & t_smooth_start < 0.7*args.t_start) = Vd_max; V_d(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) = Vd_max - (t_smooth_start(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) - 0.7*args.t_start)*Vd_max/(0.2*args.t_start); V_smooth_start = cumtrapz(V_d)*args.Ts; V_smooth_end = args.V_mean - V_smooth_start; end V_exc = [V_smooth_start, V_noise, V_smooth_end]; t_exc = args.Ts*[0:1:length(V_exc)-1]; U_exc = [t_exc; V_exc];