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