# Why are IIR Filters designed in the Filter Design Toolbox more stable than those in the Signal Processing Toolbox?

--

When designing filters you need normalized coefficients, and when they get very close or abut to 0 or 1, IIR goes unstable with the** Signal Processing **Toolbox. This effect is magnified for higher orders of the filter.

# ANSWER

Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.

The behavior observed is an expected behavior. This is a result of using the Transfer Function versus the Zeros and Poles of the filter generated by the BUTTER function in the **Signal Processing** Toolbox. They are identical mathematically but numerically the Zeros and Poles are more stable.

This limitation is mentioned in the **documentation **for the BUTTER function in Signal Processing Toolbox 6.9 (R2008a).

The resolution is illustrated below:

[b,a] = butter(6 , [25e6 29e6]/500e6 , 'bandpass') % bad design [z, p, k] = butter(6 , [25e6 29e6]/500e6 , 'bandpass'); % good design [sos,g] = zp2sos(z,p,k); Hd = dfilt.df2tsos(sos,g); fvtool(b,a,Hd, 'Fs', 500e6*2)