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pzmap - Plot zeros and poles with confidence interval

Syntax

pzmap(m)
pzmap(m,'sd',sd)
pzmap(m1,m2,m3,...)
pzmap(m1,'PlotStyle1',m2,'PlotStyle2',...,'sd',sd)
pzmap(m1,m2,m3,..,'sd',sd,'mode',mode,'axis',axis)

Description

m is any idmodel object: idarx, idgrey, idss, idproc, or idpoly.

The zeros and poles of m are graphed, with o denoting zeros and x denoting poles. Poles and zeros at infinity are ignored. For discrete-time models, zeros and poles at the origin are also ignored.

The Property/Value pairs 'sd'/sd, 'mode'/mode and `axis'/axis can appear in any order. They are explained below.

If sd has a value larger than zero, confidence regions around the poles and zeros are also graphed. The regions corresponding to sd standard deviations are marked. The default value is sd = 0. Note that the confidence regions might sometimes stretch outside the plot, but they are always symmetric around the indicated zero or pole.

If the poles and zeros are associated with a discrete-time model, a unit circle is also drawn. For continuous-time models, the real and imaginary axes are drawn.

When mi contains information about several different input/output channels, you have the following options:

mode = 'sub' splits the screen into several plots, one for each input/output channel. These are based on the InputName and OutputName properties associated with the different models.

mode = 'same' gives all plots in the same diagram. Pressing the Enter key advances the plots.

mode = 'sep' erases the previous plot before the next channel pair is treated.

The default value is mode = 'sub'.

axis = [x1 x2 y1 y2] fixes the axis scaling accordingly. axis = s is the same as

axis = [-s s -s s]

You can select the colors associated with the different models by using the argument PlotStyle. Use PlotStyle = 'b', 'g', etc. Markers and line styles are not used.

The noise input channels in m are treated as follows: Consider a model m with both measured input channels u (nu channels) and noise channels e (ny channels) with covariance matrix

where L is a lower triangular matrix. Note that m.NoiseVariance = . The model can also be described with a unit variance, using a normalized noise source v.

Then,

pzmap(m) plots the zeros and poles of the transfer function G.
pzmap(m('n')) plots the zeros and poles of the transfer function H (ny inputs and ny outputs). The input channels have names e@yname, where yname is the name of the corresponding output.
If m is a time series, that is nu= 0, pzmap(m) plots the zeros and poles of the transfer function H.
pzmap(noisecnv(m)) plots the zeros and poles of the transfer function [G H] (nu+ny inputs and ny outputs). The noise input channels have names e@yname, where yname is the name of the corresponding output.
pzmap(noisecnv(m,'norm') plots the zeros and poles of the transfer function [G HL] (nu+ny inputs and ny outputs). The noise input channels have names v@yname, where yname is the name of the corresponding output.

Examples

mbj = bj(data,[2 2 1 1 1]);
mar = armax(data,[2 2 2 1]);
pzmap(mbj,mar,'sd',3)

shows all zeros and poles of two models along with the confidence regions corresponding to three standard deviations.

pzmap - Plot zeros and poles with confidence interval

Syntax

Description

Examples

See Also

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