C06FKF (PDF version)
C06 Chapter Contents
C06 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

C06FKF

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

 Contents

    1  Purpose
    7  Accuracy

1  Purpose

C06FKF calculates the circular convolution or correlation of two real vectors of period n (using a work array for extra speed).

2  Specification

SUBROUTINE C06FKF ( JOB, X, Y, N, WORK, IFAIL)
INTEGER  JOB, N, IFAIL
REAL (KIND=nag_wp)  X(N), Y(N), WORK(N)

3  Description

C06FKF computes:
Here x and y are real vectors, assumed to be periodic, with period n, i.e., xj = x j±n = x j±2n = ; z and w are then also periodic with period n.
Note:  this usage of the terms ‘convolution’ and ‘correlation’ is taken from Brigham (1974). The term ‘convolution’ is sometimes used to denote both these computations.
If x^ , y^ , z^  and w^  are the discrete Fourier transforms of these sequences, i.e.,
x^k = 1n j=0 n-1 xj × exp -i 2πjk n , etc.,  
then z^k = n . x^k y^k  and w^k = n . x^- k y^k  (the bar denoting complex conjugate).
This routine calls the same auxiliary routines as C06PAF to compute discrete Fourier transforms.

4  References

Brigham E O (1974) The Fast Fourier Transform Prentice–Hall

5  Arguments

1:     JOB – INTEGERInput
On entry: the computation to be performed.
JOB=1
zk = j=0 n-1 x j y k-j  (convolution);
JOB=2
w k = j=0 n-1 x j y k+j  (correlation).
Constraint: JOB=1 or 2.
2:     XN – REAL (KIND=nag_wp) arrayInput/Output
On entry: the elements of one period of the vector x. If X is declared with bounds 0:N-1 in the subroutine from which C06FKF is called, then Xj  must contain xj, for j=0,1,,n-1.
On exit: the corresponding elements of the discrete convolution or correlation.
3:     YN – REAL (KIND=nag_wp) arrayInput/Output
On entry: the elements of one period of the vector y. If Y is declared with bounds 0:N-1 in the subroutine from which C06FKF is called, then Yj must contain yj, for j=0,1,,n-1.
On exit: the discrete Fourier transform of the convolution or correlation returned in the array X; the transform is stored in Hermitian form; if the components of the transform zk are written as ak+ibk, then for 0kn/2, ak is contained in Yk, and for 1kn/2-1, bk is contained in Yn-k. (See also Section 2.1.2 in the C06 Chapter Introduction.)
4:     N – INTEGERInput
On entry: n, the number of values in one period of the vectors X and Y.
Constraint: N>1.
5:     WORKN – REAL (KIND=nag_wp) arrayWorkspace
6:     IFAIL – INTEGERInput/Output
On entry: IFAIL must be set to 0, -1​ or ​1. If you are unfamiliar with this argument you should refer to Section 3.4 in How to Use the NAG Library and its Documentation for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this argument, the recommended value is 0. When the value -1​ or ​1 is used it is essential to test the value of IFAIL on exit.
On exit: IFAIL=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6  Error Indicators and Warnings

If on entry IFAIL=0 or -1, explanatory error messages are output on the current error message unit (as defined by X04AAF).
Errors or warnings detected by the routine:
IFAIL=3
On entry,N1.
IFAIL=4
On entry,JOB1 or 2.
IFAIL=-99
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
IFAIL=-399
Your licence key may have expired or may not have been installed correctly.
See Section 3.8 in How to Use the NAG Library and its Documentation for further information.
IFAIL=-999
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.

7  Accuracy

The results should be accurate to within a small multiple of the machine precision.

8  Parallelism and Performance

C06FKF is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
C06FKF makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9  Further Comments

The time taken is approximately proportional to n × logn, but also depends on the factorization of n. C06FKF is faster if the only prime factors of n are 2, 3 or 5; and fastest of all if n is a power of 2.

10  Example

This example reads in the elements of one period of two real vectors x and y, and prints their discrete convolution and correlation (as computed by C06FKF). In realistic computations the number of data values would be much larger.

10.1  Program Text

Program Text (c06fkfe.f90)

10.2  Program Data

Program Data (c06fkfe.d)

10.3  Program Results

Program Results (c06fkfe.r)


C06FKF (PDF version)
C06 Chapter Contents
C06 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2016