NAG Library Routine Document

C06FBF

+− Contents

1 Purpose

2 Specification

3 Description

4 References

5 Parameters

6 Error Indicators and Warnings

7 Accuracy

8 Further Comments

+− 9 Example

9.1 Program Text

9.2 Program Data

9.3 Program Results

1 Purpose

C06FBF calculates the discrete Fourier transform of a Hermitian sequence of

n

complex data values (using a work array for extra speed).

2 Specification

SUBROUTINE C06FBF (

X, N, WORK, IFAIL)

INTEGER	N, IFAIL
REAL (KIND=nag_wp)	X(N), WORK(N)

3 Description

Given a Hermitian sequence of

n

complex data values

z_{j}

(i.e., a sequence such that

z_{0}

is real and

z_{n - j}

is the complex conjugate of

z_{j}

, for

j = 1, 2, \dots, n - 1

), C06FBF calculates their discrete Fourier transform defined by

{\hat{x}}_{k} = \frac{1}{\sqrt{n}} \sum_{j = 0}^{n - 1} z_{j} \times \exp (- i \frac{2 π j k}{n}), k = 0, 1, \dots, n - 1 .

(Note the scale factor of

\frac{1}{\sqrt{n}}

in this definition.) The transformed values

{\hat{x}}_{k}

are purely real (see also the C06 Chapter Introduction).

To compute the inverse discrete Fourier transform defined by

{\hat{y}}_{k} = \frac{1}{\sqrt{n}} \sum_{j = 0}^{n - 1} z_{j} \times \exp (+ i \frac{2 π j k}{n}),

this routine should be preceded by forming the complex conjugates of the

{\hat{z}}_{k}

; that is,

x (k) = - x (k)

, for

k = n / 2 + 2, \dots, n

C06FBF uses the fast Fourier transform (FFT) algorithm (see Brigham (1974)). There are some restrictions on the value of

n

(see Section 5).

4 References

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

5 Parameters

1: X(N) – REAL (KIND=nag_wp) arrayInput/Output: On entry: the sequence to be transformed stored in Hermitian form. If the data values $z_{j}$ are written as $x_{j} + i y_{j}$ , and if X is declared with bounds $(0 : N - 1)$ in the subroutine from which C06FBF is called, then for $0 \leq j \leq n / 2$ , $x_{j}$ is contained in $X (j)$ , and for $1 \leq j \leq (n - 1) / 2$ , $y_{j}$ is contained in $X (n - j)$ . (See also Section 2.1.2 in the C06 Chapter Introduction and Section 9.)

On exit: the components of the discrete Fourier transform ${\hat{x}}_{k}$ . If X is declared with bounds $(0 : N - 1)$ in the subroutine from which C06FBF is called, then ${\hat{x}}_{k}$ is stored in $X (k)$ , for $k = 0, 1, \dots, n - 1$ .
2: N – INTEGERInput: On entry: $n$ , the number of data values. The largest prime factor of N must not exceed $19$ , and the total number of prime factors of N, counting repetitions, must not exceed $20$ .
Constraint: $N > 1$ .
3: WORK(N) – REAL (KIND=nag_wp) arrayWorkspace
4: IFAIL – INTEGERInput/Output: On entry: IFAIL must be set to $0$ , $- 1 or 1$ . If you are unfamiliar with this parameter you should refer to Section 3.3 in the Essential Introduction 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 parameter, 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

- 1

, explanatory error messages are output on the current error message unit (as defined by X04AAF).

Errors or warnings detected by the routine:

$IFAIL = 1$: At least one of the prime factors of N is greater than $19$ .

$IFAIL = 2$: N has more than $20$ prime factors.

$IFAIL = 3$

On entry,

N \leq 1

$IFAIL = 4$: An unexpected error has occurred in an internal call. Check all subroutine calls and array dimensions. Seek expert help.

7 Accuracy

Some indication of accuracy can be obtained by performing a subsequent inverse transform and comparing the results with the original sequence (in exact arithmetic they would be identical).

8 Further Comments

The time taken is approximately proportional to

n \times \log n

, but also depends on the factorization of

n

. C06FBF is faster if the only prime factors of

n

are

2

3

5

; and fastest of all if

n

is a power of

2

9 Example

This example reads in a sequence of real data values which is assumed to be a Hermitian sequence of complex data values stored in Hermitian form. The input sequence is expanded into a full complex sequence and printed alongside the original sequence. The discrete Fourier transform (as computed by C06FBF) is printed out. It then performs an inverse transform using C06FAF and conjugation, and prints the sequence so obtained alongside the original data values.

NAG Library Routine DocumentC06FBF