compute the finite linear convolution of two arrays of samples - Maple Help

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SignalProcessing[Convolution] - compute the finite linear convolution of two arrays of samples

Calling Sequence

Convolution(A, B)

Parameters

A, B

-

Arrays of real numeric sample values

Description

• 

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+N1 and having datatype float[8], which is then returned.

• 

The convolution is defined by the formula

Ck=i=1kAiBki+1

  

for each k from 1 to M&plus;N1, with Aj&equals;0 for M<j and Bj&equals;0 for N<j.

• 

Before the code performing the computation runs, A and B are converted to datatype float[8] 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&plus;N1 having datatype float[8].

Thread Safety

• 

The SignalProcessing[Convolution] command is thread-safe as of Maple 17.

• 

For more information on thread safety, see index/threadsafe.

Examples

withSignalProcessing&colon;

a:=Array1&comma;2&comma;3&comma;&apos;datatype&apos;&equals;&apos;float&apos;8

a:=1.2.3.

(1)

b:=Array1&comma;1&comma;1&comma;1&comma;&apos;datatype&apos;&equals;&apos;float&apos;8

b:=1.1.1.1.

(2)

Convolutiona&comma;b

1.1.2.2.1.3.

(3)

c:=Array1..numelemsa&plus;numelemsb1&comma;&apos;datatype&apos;&equals;&apos;float&apos;8&colon;

Convolutiona&comma;b&comma;&apos;container&apos;&equals;c

1.1.2.2.1.3.

(4)

c

1.1.2.2.1.3.

(5)

See Also

SignalProcessing[AutoCorrelation], SignalProcessing[CrossCorrelation]


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