Digital Filter Design

Classes
class	gr::filter::firdes
	Finite Impulse Response (FIR) filter design functions. More...

Enumerations
enum	gr::filter::firdes::win_type {   gr::filter::firdes::WIN_NONE = -1, gr::filter::firdes::WIN_HAMMING = 0, gr::filter::firdes::WIN_HANN = 1, gr::filter::firdes::WIN_BLACKMAN = 2,   gr::filter::firdes::WIN_RECTANGULAR = 3, gr::filter::firdes::WIN_KAISER = 4, gr::filter::firdes::WIN_BLACKMAN_hARRIS = 5, gr::filter::firdes::WIN_BLACKMAN_HARRIS = 5,   gr::filter::firdes::WIN_BARTLETT = 6, gr::filter::firdes::WIN_FLATTOP = 7 }

Functions
FILTER_API std::vector< double >	gr::filter::pm_remez (int order, const std::vector< double > &bands, const std::vector< double > &ampl, const std::vector< double > &error_weight, const std::string filter_type="bandpass", int grid_density=16) throw (std::runtime_error)
	Parks-McClellan FIR filter design using Remez algorithm. More...

Detailed Description

Enumeration Type Documentation

enum gr::filter::firdes::win_type

Enumerator
WIN_NONE	don't use a window
WIN_HAMMING	Hamming window; max attenuation 53 dB.
WIN_HANN	Hann window; max attenuation 44 dB.
WIN_BLACKMAN	Blackman window; max attenuation 74 dB.
WIN_RECTANGULAR	Basic rectangular window.
WIN_KAISER	Kaiser window; max attenuation a function of beta, google it.
WIN_BLACKMAN_hARRIS	Blackman-harris window.
WIN_BLACKMAN_HARRIS	alias to WIN_BLACKMAN_hARRIS for capitalization consistency
WIN_BARTLETT	Barlett (triangular) window.
WIN_FLATTOP	flat top window; useful in FFTs

Function Documentation

FILTER_API std::vector<double> gr::filter::pm_remez	(	int	order,
		const std::vector< double > &	bands,
		const std::vector< double > &	ampl,
		const std::vector< double > &	error_weight,
		const std::string	filter_type = "bandpass",
		int	grid_density = 16
	)
throw	(	std::runtime_error
	)

Parks-McClellan FIR filter design using Remez algorithm.

Calculates the optimal (in the Chebyshev/minimax sense) FIR filter inpulse reponse given a set of band edges, the desired reponse on those bands, and the weight given to the error in those bands.

Parameters

order	filter order (number of taps in the returned filter - 1)
bands	frequency at the band edges [ b1 e1 b2 e2 b3 e3 ...]
ampl	desired amplitude at the band edges [ a(b1) a(e1) a(b2) a(e2) ...]
error_weight	weighting applied to each band (usually 1)
filter_type	one of "bandpass", "hilbert" or "differentiator"
grid_density	determines how accurately the filter will be constructed. \ The minimum value is 16; higher values are slower to compute.

Frequency is in the range [0, 1], with 1 being the Nyquist frequency (Fs/2)

Returns

vector of computed taps

Exceptions

std::runtime_error

if args are invalid or calculation fails to converge.