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Symp_Filter_SubSys.m
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Symp_Filter_SubSys.m
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classdef Symp_Filter_SubSys < matlab.System
% untitled2 Add summary here
%
% This template includes the minimum set of functions required
% to define a System object with discrete state.
% Public, tunable properties
properties
end
properties(DiscreteState)
end
% Pre-computed constants
properties(Access = private)
end
methods(Access = protected)
% function setupImpl(Symp_Filter_SubSys)
% % Perform one-time calculations, such as computing constants
% Symp_Filter_SubSys.pFileID = fopen(Symp_Filter_SubSys.Symp_Filter_SubSys,'wb');
% if Symp_Filter_SubSys.pFileID < 0
% error('Opening the file failed');
% end
% end
function [Symp_A1,Symp_A2,Symp_A3,Symp_A4,Symp_A5,Symp_B1,Symp_B2,Symp_B3,Symp_B4,Symp_B5,Symp_S1,Symp_S2] = stepImpl(obj,t_f,Time_series)
% Implement algorithm. Calculate y as a function of input u and
% discrete states.
eval_time = t_f + 2.0;
current_time = getCurrentTime(obj);
if current_time <= eval_time
Symp_A1 = Time_series(1);
Symp_A2 = Time_series(2);
Symp_A3 = Time_series(3);
Symp_A4 = Time_series(4);
Symp_A5 = Time_series(5);
Symp_B1 = Time_series(6);
Symp_B2 = Time_series(7);
Symp_B3 = Time_series(8);
Symp_B4 = Time_series(9);
Symp_B5 = Time_series(10);
% Symp_S1 = Time_series(11);
% Symp_S2 = Time_series(12);
else
Symp_A1 = 0;
Symp_A2 = 0;
Symp_A3 = 0;
Symp_A4 = 0;
Symp_A5 = 0;
Symp_B1 = 0;
Symp_B2 = 0;
Symp_B3 = 0;
Symp_B4 = 0;
Symp_B5 = 0;
end
Symp_S1 = Time_series(11);
Symp_S2 = Time_series(12);
end
% symp_min = zeros(1,10);
% symp_max = zeros(1,10);
% symp_out = zeros(1,10);
% symp_min = [];
% symp_max = [];
% symp_out = [];
% flag =0;
% for i = 1:10
% % 滞后症状判据：在eval_time之前小于零，且之后大于零的信号，置为零
% % 提取在t_f <= t <= t_f + 2s内出现症状的最大和最小值并保持输出
% current_time = getCurrentTime(obj);
% if current_time > eval_time && current_time < 20.05
% if Time_series_dis_der(i)~=0 && Time_series(i)~=0
% flag = i;
% % Time_series(i)=0;
% % Time_series(i) = 0; % 因为在这里信号变成了0，微分也为0，不满足当前条件，所以下一时刻又输出了原信号
% end
% % Time_series(flag) = 0;
% end
% end
% Symp_A1 = Time_series(1);
% Symp_A2 = Time_series(2);
% Symp_A3 = Time_series(3);
% Symp_A4 = Time_series(4);
% Symp_A5 = Time_series(5);
% Symp_B1 = Time_series(6);
% Symp_B2 = Time_series(7);
% Symp_B3 = Time_series(8);
% Symp_B4 = Time_series(9);
% Symp_B5 = Time_series(10);
% Symp_S1 = Time_series(11);
% Symp_S2 = Time_series(12);
% end
% Out = Time_series(1);
% Symp_A1 = symp_out(1);
% Symp_A2 = symp_out(2);
% Symp_A3 = symp_out(3);
% Symp_A4 = symp_out(4);
% Symp_A5 = symp_out(5);
% Symp_B1 = symp_out(6);
% Symp_B2 = symp_out(7);
% Symp_B3 = symp_out(8);
% Symp_B4 = symp_out(9);
% Symp_B5 = symp_out(10);
% Symp_S1 = Time_series(11);
% Symp_S2 = Time_series(12);
function resetImpl(obj)
% Initialize / reset discrete-state properties
end
end
end