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Interface JSci.maths.wavelet.Filter
- public interface Filter
This interface is used to define wavelet filters.
It is fairly general to accomodate just about any
filter (except complex ones). Since changing
an interface is painful, it must be as general
as possible to start with. Therefore it doesn't
assume that you are using dyadic wavelets (for
example) and so, some object will implement
somewhat redundant method that builds on the
dyadic grid (for simplicity).
-
highpass(double[])
- Highpass filters are normalized
in order to get L2 orthonormality of the
resulting wavelets (when it applies).
-
highpass(double[], double[])
- Highpass filters are normalized
in order to get L2 orthonormality of the
resulting wavelets (when it applies).
-
lowpass(double[])
- lowpass filter
-
lowpass(double[], double[])
- lowpass filter
-
previousDimension(int)
- This method return the number of "scaling"
functions at the previous scale given a
number of scaling functions.
lowpass
public abstract double[] lowpass(double x[])
- lowpass filter
highpass
public abstract double[] highpass(double y[])
- Highpass filters are normalized
in order to get L2 orthonormality of the
resulting wavelets (when it applies).
See the class DiscreteHilbertSpace for
an implementation of the L2 integration.
lowpass
public abstract double[] lowpass(double x[],
double param[])
- lowpass filter
- Parameters:
- param - a parameter for the filter
highpass
public abstract double[] highpass(double y[],
double param[])
- Highpass filters are normalized
in order to get L2 orthonormality of the
resulting wavelets (when it applies).
See the class DiscreteHilbertSpace for
an implementation of the L2 integration.
- Parameters:
- param - a parameter for the filter
previousDimension
public abstract int previousDimension(int k)
- This method return the number of "scaling"
functions at the previous scale given a
number of scaling functions. The answer
is always smaller than the provided value
(about half since this is a dyadic
implementation). This relates to the same idea
as the "filter type".
However this method is used in the context
of signal processing for performance
reasons.
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