我正在使用mpiir_l2()用户Matt L的博士论文来设计 IIR 滤波器。我将分子和分母系数的数量都设置为相同的值（在$100$和$300$）。最大磁极半径为$0.98$. 我的观察是结果实际上是一个 FIR 滤波器，分母系数总是$[1, 0, 0, ...]$. 基本上，结果等于lslevin()同一来源的最小二乘 FIR 设计的函数。

显然，我的滤波器规范中的某些内容使 FIR 解决方案比任何 IIR 滤波器具有更好的错误。该规范是数值优化的结果，在人眼看来非常随机，所以我不确定要寻找哪些属性。

有没有办法从这个函数中得到一个真正的 IIR 滤波器？我想比较相同规格的 IIR 和 FIR 滤波器，看看哪个更好。现在，当结果基本相同时，我真的无法比较。

编辑：这是一个示例脚本和相应的所需响应。看来我必须为此使用第三方托管网站，抱歉。

close all;
clear all;

% loads the specification, weights and frequencies as three vectors
% the sepcification has a relevant band that is padded with zeros to both
% sides. There is a "don't care" gap between the relevant band and the
% zeros.
load 'desiredResponse.mat' % loads Ws, freqs, desiredResponse 

% search area
allowedOrder = 1:1:3;       % numerator and denominator order 
allowedShifts = 0:0.125:2;      % linear phase term

% other variables
Fs = 48000;
normalFreqs = freqs / Fs * 2 * pi; % normalized frequencies
poleRadius = 0.98;

% preallcoate for the search
lowestError = inf;
bestNum = [];
bestDenom = [];
errors = zeros(length(allowedOrder), length(allowedShifts));
orders = zeros(length(allowedOrder), length(allowedShifts));
shifts = zeros(length(allowedOrder), length(allowedShifts));

% search for best aproximation
for nl = 1:length(allowedOrder)
    ord = allowedOrder(nl);
    for ns = 1:length(allowedShifts)
        orders(nl, ns) = ord;
        shifts(nl, ns) = allowedShifts(ns);
        % add the linear phase shift
        phaseShiftTerm = exp(-1i * shifts(nl, ns) * (ord-1)/2/Fs * 2 * pi * freqs);
        D = desiredResponse .* phaseShiftTerm;

        % design the filter (change denominator order here, if you like)
        [num,denom] = mpiir_l2(ord, ord, normalFreqs, D, Ws, poleRadius);

        % calculate filter response
        H = freqz(num, denom, freqs, Fs);
        % calculate the weighted error
        errors(nl, ns) = sum(Ws .* abs(H - D).^2);

        if errors(nl, ns) < lowestError
            lowestError = errors(nl, ns);
            bestNum = num;
            bestDenom = denom;
        end
    end
end