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    %% Analyze Time-Series Models
% This example shows how to analyze time-series models.
%%
% A time-series model has no inputs. However, you can use many response
% computation commands on such models. The software treats (implicitly) the
% noise source |e(t)| as a measured input. Thus,
% |step(sys)|  plots the step response assuming that the
% step input was applied to the noise channel |e(t)|.
%%
% To avoid ambiguity in how the software treats a time-series model, you
% can transform it explicitly into an input-output model using |noise2meas|.
% This command causes the noise input |e(t)| to be treated as a measured
% input and transforms the linear time series model with |Ny| outputs into an
% input-output model with |Ny| outputs and |Ny| inputs. You can use the
% resulting model with commands, such as, |bode|, |nyquist|, and |iopzmap| to
% study the characteristics of the |H| transfer function. 
%%
% Estimate a time-series model.
load iddata9
sys = ar(z9,4);
%%
% Convert the time-series model to an input-output model.
iosys = noise2meas(sys);
%%
% Plot the step response of |H|. 
step(iosys);
%%
% Plot the poles and zeros of |H|.
iopzmap(iosys);
%%
% Calculate and plot the time-series spectrum directly without converting
% to an input-output model.
spectrum(sys);
%%
% The command plots the time-series spectrum amplitude $\Phi (\omega ) =
% {\left\| {H(\omega )} \right\|^2}$.
%