input signal to be convolved
filter kernel (will be read only once)
length of filter kernel (static)
threshold for input samples within kernel range. convolution is only applied to those frames whose absolute difference to the centre inter
a trigger signal that determines logical "boundaries" in the input signal. The convolution is truncated to the left and right of the boundary positions, making it possible to perform convolutions on windowed signals.
a trigger signal that determines logical "boundaries" in the input signal.
a trigger signal that determines logical "boundaries" in the input signal. The convolution is truncated to the left and right of the boundary positions, making it possible to perform convolutions on windowed signals.
input signal to be convolved
filter kernel (will be read only once)
Abstract method which must be implemented by creating the actual UGen
s
during expansion.
Abstract method which must be implemented by creating the actual UGen
s
during expansion. This method is at most called once during graph
expansion
the expanded object (depending on the type parameter U
)
length of filter kernel (static)
threshold for input samples within kernel range.
threshold for input samples within kernel range. convolution is only applied to those frames whose absolute difference to the centre inter
input signal to be convolved
filter kernel (will be read only once)
length of filter kernel (static)
threshold for input samples within kernel range. convolution is only applied to those frames whose absolute difference to the centre inter
a trigger signal that determines logical "boundaries" in the input signal. The convolution is truncated to the left and right of the boundary positions, making it possible to perform convolutions on windowed signals.