compute the finite linear convolution of two arrays of samples
Arrays of real numeric sample values
container : Array, predefined Array for holding result
The Convolution(A, B) command computes the convolution of the Arrays A and B of length M and N respectively, storing the result in a Array C of length M+N−1 and having datatype float, which is then returned.
The convolution is defined by the formula
for each k from 1 to M+N−1, with Aj=0 for M<j and Bj=0 for N<j.
Before the code performing the computation runs, A and B are converted to datatype float if they do not have that datatype already. For this reason, it is most efficient if A and B have this datatype beforehand.
If the container=C option is provided, then the results are put into C and C is returned. With this option, no additional memory is allocated to store the result. The container must be an Array of size M+N−1 having datatype float.
The SignalProcessing[Convolution] command is thread-safe as of Maple 17.
For more information on thread safety, see index/threadsafe.
a ≔ Array⁡1,2,3,'datatype'='float'8
b ≔ Array⁡1,−1,1,−1,'datatype'='float'8
c ≔ Array⁡1..numelems⁡a+numelems⁡b−1,'datatype'='float'8:
The SignalProcessing[Convolution] command was introduced in Maple 17.
For more information on Maple 17 changes, see Updates in Maple 17.
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