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Owning Class: modeling and prediction
Requires: MathScript RT Module
[b, a] = iir_steigmcbride(x, m, n)
[b, a] = iir_steigmcbride(x, m, n, t)
[b, a] = iir_steigmcbride(x, m, n, t, aa)
[b, a] = iir_steigmcbride(x, u, m, n)
[b, a] = iir_steigmcbride(x, u, m, n, t)
[b, a] = iir_steigmcbride(x, u, m, n, t, aa)
Legacy Name: stmcb
Uses a Steiglitz-McBride iteration to design a linear filter model.
Name | Description |
---|---|
x | Specifies the output of the filter. x is a vector. |
u | Specifies the input of the filter. u is a vector of the same length as x. If you do not specify u, LabVIEW views x as the impulse response of the filter. |
m | Specifies the numerator order. m is a positive integer. |
n | Specifies the denominator order. n is a positive integer. |
t | Specifies the number of iterations. t is a positive integer. The default is 5. |
aa | Specifies the initial value of the denominator coefficients. aa is a vector with length n. The default is prony(x, 0, n). |
Name | Description |
---|---|
b | Returns the forward filter coefficients. b is a vector. |
a | Returns the backward filter coefficients. a is a vector. |
The following table lists the support characteristics of this function.
Supported in the LabVIEW Run-Time Engine | Yes |
Supported on RT targets | Yes |
Suitable for bounded execution times on RT | Not characterized |
b1 = rand(1, 3)
a1 = [1, rand(1, 3)]
h = impzd(b1, a1, 10);
[b2, a2] = iir_steigmcbride(h, 2, 3)