% error: b = fir2(n, f, m [, grid_n [, ramp_n]] [, window]) % % Produce an FIR filter of order n with arbitrary frequency response, % returning the n+1 filter coefficients in b. % % n: order of the filter (1 less than the length of the filter) % f: frequency at band edges % f is a vector of nondecreasing elements in [0,1] % the first element must be 0 and the last element must be 1 % if elements are identical, it indicates a jump in freq. response % m: magnitude at band edges % m is a vector of length(f) % grid_n: length of ideal frequency response function % defaults to 512, should be a power of 2 bigger than n % ramp_n: transition width for jumps in filter response % defaults to grid_n/20; a wider ramp gives wider transitions % but has better stopband characteristics. % window: smoothing window % defaults to hamming(n+1) row vector % returned filter is the same shape as the smoothing window % % To apply the filter, use the return vector b: % y=filter(b,1,x); % Note that plot(f,m) shows target response. % % Example: % f=[0, 0.3, 0.3, 0.6, 0.6, 1]; m=[0, 0, 1, 1/2, 0, 0]; % [h, w] = freqz(fir2(100,f,m)); % plot(f,m,';target response;',w/pi,abs(h),';filter response;');

- hamming % Return the filter coefficients of a Hamming window of length @var{m}.
- window % Create a @var{n}-point windowing from the function @var{f}. The

- fir1 % error: b = fir1(n, w [, type] [, window] [, noscale])

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