RK4Detector Class Reference

Use the fourth order Runge-Kutta method to calculate the output. More...

#include <detectors.h>

Inheritance diagram for RK4Detector:

Collaboration diagram for RK4Detector:

Public Member Functions
	RK4Detector (const parameter_t f, const parameter_t mu, const parameter_t d, const parameter_t sr, const parameter_t detBw, const parameter_t gain)
virtual void	reset ()
	Reset internal values to 0 This is invoked when Detect.seek() is called.
virtual void	process (discriminator_t *target, const inputSample_t *start, const std::size_t count) override
	Method to process audio using fourth order Runge-Kutta approximation. More...
Public Member Functions inherited from AbstractDetector
	AbstractDetector (parameter_t f, parameter_t mu, parameter_t d, parameter_t sr, parameter_t detBw, parameter_t gain)
void	processAudio (discriminator_t *target, const inputSample_t *start, std::size_t count)
	Process audio using the numerical method appropriate to the derived class. More...
bool	searchNormalize (parameter_t searchStart, parameter_t searchEnd, const parameter_t toneDuration, const parameter_t forcing_amplitude)
	Normalise the detector frequency using an iterative scheme. More...
bool	amplitudeNormalize (const parameter_t forcing_amplitude)
	Set the detector's a and iScale attributes by profiling an ideal detector response. More...
void	scaleAmplitude ()
	Calculate amplitude scale factor.
void	generateTone (inputSample_t *tone, const std::size_t duration, const parameter_t frequency)
	Generate a sine tone. More...
parameter_t	getW (void) const
	Find the speficied characteristic frequency for this detector (post-modulation and -normalisation) More...

Private Attributes
std::complex< parameter_t >	zp
	previous z value
std::complex< parameter_t >	zpp
	z value two samples ago
inputSample_t	xp
	previous audio input sample
inputSample_t	xpp
	audio input sample two samples ago

Additional Inherited Members
Protected Member Functions inherited from AbstractDetector
template<class Archive >
void	save (Archive &archive) const
	Save the DetectorBank as a cereal archive. More...
template<class Archive >
void	load (Archive &archive)
	Load the DetectorBank from a cereal archive. More...
void	makeScaleVectors ()
	Make freq and factor vectors for given method and normalisation.
void	getScaleValue (const parameter_t fr)
	Get a scale value for a given frequency.
Static Protected Member Functions inherited from AbstractDetector
static const parameter_t	getLyapunov (const parameter_t bw, const parameter_t amp)
	Find the first Lyapunov coefficient required for a given bandwidth, with a given forcing amplitude. More...
Protected Attributes inherited from AbstractDetector
parameter_t	w
	Characteristic frequency.
parameter_t const	mu
	Distance from the bifurcation point.
parameter_t const	d
	Detector damping factor.
parameter_t const	sr
	Sample rate.
parameter_t const	detBw
	Detector bandwidth.
parameter_t const	gain
	Detector gain.
discriminator_t	aScale
	Amplitude scaling factor.
parameter_t	iScale
	Scaling factor for imaginary part.
parameter_t	b
	Detector's first Lyapunov coefficent.
discriminator_t	scale
	Detector's scale factor.
bool	nrml { false }
	If search normalisation has been applied.
std::vector< parameter_t >	detScaleFreqs
std::vector< discriminator_t >	detScaleFactors
Static Protected Attributes inherited from AbstractDetector
static constexpr int	maxNormIterations { 100 }
	The maximum number of iterations to find best response during search_normalization.
static constexpr double	normConverged { 1.0028922878693671 }
	Ratio of discovered frequency to specification frequency to be considered "close enough" during seach_normalization. More...
static const std::array< std::vector< parameter_t >, 8 >	scaleFreqs
static const std::array< std::vector< discriminator_t >, 8 >	scaleFactors

Detailed Description

Use the fourth order Runge-Kutta method to calculate the output.

Uses the discrete Runge-Kutta method to solve the first order differential equation \(y'=f(y, t)\). Let:

\begin{eqnarray*} k_0 & = & f(y_n, n-2) \\ k_1 & = & f(y_n + k_0\delta, n-1) \\ k_2 & = & f(y_n + k_1\delta, n) \\ k_3 & = & f(y_n + k_22\delta, n) \end{eqnarray*}

where \(\delta\) is the time step between samples,

then:

\[ y_{n+1} = y_n + \frac\delta 3(k_0 + 2k_1 + 2k_2 + k_3). \]

This procedure is used iterativey to find output samples of the Hopf bifurcation

\[\dot z=(\mu+j\omega_0)z + b|z|^2z + X\]

with control parameter \(\mu\), first Lyapunov coeffcient \(b\) (real) and driving force \(X\). For a supercritical bifurcation, \(b < 0\). \(b = 0\) yeilds a degenerate ("Bautin") bifurcation, and \(b > 0\) yeilds a subcritical bifurcation which is unstable.

Definition at line 291 of file detectors.h.

Constructor & Destructor Documentation

RK4Detector()

RK4Detector::RK4Detector	(	const parameter_t	f,
		const parameter_t	mu,
		const parameter_t	d,
		const parameter_t	sr,
		const parameter_t	detBw,
		const parameter_t	gain
	)

Parameters

f	Detector centre frequency (Hz)
mu	Detector control parameter. (Setting mu = 0 positions the system at the bifurcation point)
d	Detector damping ratio
sr	Sample rate of input audio
detBw	Detector bandwidth
gain	Detector gain

Member Function Documentation

process()

virtual void RK4Detector::process ( discriminator_t *  target, const inputSample_t *  start, const std::size_t  count  )

overridevirtual

Method to process audio using fourth order Runge-Kutta approximation.

Called by runChannels() in DetectorBank.

Parameters

target	Output array. This should have the correct dimensions for your desired detector bank: height = number of detectors, length = length of audio input.
start	Current audio sample
count	Number of frames to process

Implements AbstractDetector.

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The documentation for this class was generated from the following file:

• /home/keziah/onsets/DetectorBank/src/detectors.h