name: Reflection : public AlgorithmBase


g++ [flags ...] file ... -l /isip/tools/lib/$ISIP_BINARY/lib_algo.a

#include <Reflection.h>

Reflection(ALGORITHM algorithm = DEF_ALGORITHM, IMPLEMENTATION implementation = DEF_IMPLEMENTATION, long order = DEF_ORDER, float dyn_range = DEF_DYN_RANGE);
boolean eq(const Reflection& arg);
boolean setAlgorithm(ALGORITHM algorithm);
boolean set(ALGORITHM algo = DEF_ALGORITHM, IMPLEMENTATION impl = DEF_IMPLEMENTATION, long order = DEF_ORDER, float dyn_range = DEF_DYN_RANGE);
quick start:

Reflection refl;
VectorFloat in_vec(L"1.0, 2,0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0");
VectorFloat refl_coef;
refl.set(Reflection::AUTOCORRELATION, Reflection::DURBIN, 4, -40);
refl.compute(refl_coef, in_vec);

The Reflection class is used to calculate or convert linear prediction coefficients. It is one of several classes that provide a complete inventory of linear prediction manipulations. See the prediction coefficient class
Prediction.h for a more detailed explanation of linear prediction. The algorithm and implementation choices are shown below:

The step-up algorithm is defined in: Some of the algorithms used in reflection coefficient class compute coefficients directly (LATTICE) while others compute both reflection and prediction coefficients simultaneously (AUTOCORRELATION).


public constants:

error codes:

protected data:

required public methods:

class-specific public methods:

private methods: