qlibs::smootherALNF Class Reference

Adaptive Filter LMS. More...

#include <smoother.hpp>

Inheritance diagram for qlibs::smootherALNF:

Public Member Functions
virtual	~smootherALNF ()
bool	setup (const real_t a, const real_t m, const size_t wsize, real_t *window, real_t *weights, real_t *w1=nullptr)
	Setup an initialize the Adaptive Filter LMS.
template<size_t windowSize>
bool	setup (const real_t a, const real_t m, real_t(&window)[windowSize], real_t(&weights)[windowSize], real_t(&w1)[windowSize])
	Setup an initialize the Adaptive Filter LMS.
template<size_t windowSize>
bool	setup (const real_t a, real_t(&window)[windowSize], real_t(&weights)[windowSize])
	Setup an initialize the Adaptive Filter LMS.
real_t	smooth (const real_t x) override
	Perform the smooth operation recursively for the input signal x.
Public Member Functions inherited from qlibs::smoother
virtual	~smoother ()
bool	isInitialized (void) const
	Check if the smoother filter is initialized.
bool	reset (void)
	Reset the the smoother filter.

Detailed Description

Adaptive Filter LMS.

Constructor & Destructor Documentation

~smootherALNF()

virtual qlibs::smootherALNF::~smootherALNF ( )

inlinevirtual

Member Function Documentation

setup() [1/3]

bool smootherALNF::setup	(	const real_t	a,
		const real_t	m,
		const size_t	wsize,
		real_t *	window,
		real_t *	weights,
		real_t *	w1 = nullptr )

Setup an initialize the Adaptive Filter LMS.

Parameters

[in]	a	Learning rate [ 0 < a < 1 ]
[in]	m	Momentum [ 0 < m < 1 ]
[in]	wsize	The size of the window array
[in]	window	An array to store the window samples.
[in]	weights	An array to store the filter weights
[in]	w1	An array to keep previous estimated wights. To ignore pass nullptr as argument.

Returns

true on success, otherwise return false.

setup() [2/3]

template<size_t windowSize>

bool qlibs::smootherALNF::setup ( const real_t a, const real_t m, real_t(&) window[windowSize], real_t(&) weights[windowSize], real_t(&) w1[windowSize] )

inline

Setup an initialize the Adaptive Filter LMS.

Parameters

[in]	a	Learning rate [ 0 < a < 1 ]
[in]	m	Momentum [ 0 < m < 1 ]
[in]	window	An array to store the window samples.
[in]	weights	An array to store the filter weights
[in]	w1	An array to keep previous estimated wights.

Returns

true on success, otherwise return false.

setup() [3/3]

template<size_t windowSize>

bool qlibs::smootherALNF::setup ( const real_t a, real_t(&) window[windowSize], real_t(&) weights[windowSize] )

inline

Setup an initialize the Adaptive Filter LMS.

Parameters

[in]	a	Learning rate [ 0 < a < 1 ]
[in]	window	An array to store the window samples.
[in]	weights	An array to store the filter weights.

Returns

true on success, otherwise return false.

smooth()

real_t smootherALNF::smooth ( const real_t x )

overridevirtual

Perform the smooth operation recursively for the input signal x.

Precondition

Instance must be previously initialized

Parameters

[in]

x

A sample of the input signal.

Returns

The smoothed output.

Implements qlibs::smoother.