Scilab 6.0.2
      
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 - Signal Processing
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 - How to design an elliptic filter
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 - wfir
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 - yulewalk
 - zpbutt
 - zpch1
 - zpch2
 - zpell
 
Please note that the recommended version of Scilab is 2026.0.0. This page might be outdated.
See the recommended documentation of this function
lev
Yule-Walker equations (Levinson's algorithm)
Syntax
[ar, sigma2, rc]=lev(r)
Arguments
- r
 correlation coefficients
- ar
 auto-Regressive model parameters
- sigma2
 scale constant
- rc
 reflection coefficients
Description
This function resolves the Yule-Walker equations using Levinson's algorithm. Generally, it is used to estimate the coefficients of an autoregressive process.
Example
b=1; //numerator a=[1 -0.7 0.8]; //denominator x=[1 zeros(1,99)]; //input=impulse data=filter(b,a,x); //real data a2=lev(data); //modelized data a2=a2/a2(1); //normalization m_data=filter(1,a2,x); // Compare real data and modelized data plot(data,"color","blue","lineStyle","none","marker","d"); plot(m_data,"color","red","lineStyle","none","marker","d");

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