matlab/ensemble__stochastic_2examples_2logistic2_8m_source.html

 clear all;
 addpath('..');
 addpath('../../discrete_discrete');
 addpath('../../discrete_discrete/examples');

 logistic;
 close all;

 ensemble_size = 5;
 next_func = @(x) next_func(x,0);

 [estimates_enkf,covariances_enkf] = enkf_stochastic(next_func,state_count,sensor_count,...
     outputs,ensemble_size,C,R_d,Q_d,P_0,x_0, measurements);

 h = figure;
 hold on;
 plot(0:dt:(100-1)*dt,measurements(1:100),'LineWidth',2);
 plot(0:dt:(100-1)*dt,process_noise_data(1:100),'LineWidth',2);
 plot(0:dt:(100-1)*dt,estimates_enkf(1:100),'LineWidth',2);
 legend('Measurement','Real data','Estimate');
 xlabel('Time')
 ylabel('Population')
enkf_stochastic
function enkf_stochastic(in func, in state_count, in sensor_count, in measurement_count, in ensemble_size, in C, in R, in Q, in P_0, in x_0, in measurements)