nag_sum_fft_hermitian_1d_rfmt (c06fb) uses the fast Fourier transform (FFT) algorithm (see Brigham (1974)). There are some restrictions on the value of

n

(see Arguments).

References

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

Parameters

Compulsory Input Parameters

1: $x (n)$ – double array: 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 function from which nag_sum_fft_hermitian_1d_rfmt (c06fb) 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 Real transforms in the C06 Chapter Introduction and Example.)

Optional Input Parameters

1: $n$ – int64int32nag_int scalar: Default: the dimension of the array x.
$n$ , 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: $n > 1$ .

Output Parameters

1: $x (n)$ – double array: The components of the discrete Fourier transform ${\hat{x}}_{k}$ . If x is declared with bounds $(0 : n - 1)$ in the function from which nag_sum_fft_hermitian_1d_rfmt (c06fb) is called, then ${\hat{x}}_{k}$ is stored in $x (k)$ , for $k = 0, 1, \dots, n - 1$ .
2: $ifail$ – int64int32nag_int scalar: $ifail = 0$ unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

Errors or warnings detected by the function:

$ifail = 1$: 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 function calls and array dimensions. Seek expert help.

$ifail = - 99$: An unexpected error has been triggered by this routine. Please contact NAG.

$ifail = - 399$: Your licence key may have expired or may not have been installed correctly.

$ifail = - 999$: Dynamic memory allocation failed.

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).

Further Comments

The time taken is approximately proportional to

n \times \log (n)

, but also depends on the factorization of

n

. nag_sum_fft_hermitian_1d_rfmt (c06fb) is faster if the only prime factors of

n

are

2

3

5

; and fastest of all if

n

is a power of

2

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 nag_sum_fft_hermitian_1d_rfmt (c06fb)) is printed out. It then performs an inverse transform using nag_sum_fft_real_1d_rfmt (c06fa) and conjugation, and prints the sequence so obtained alongside the original data values.

Open in the MATLAB editor: c06fb_example

function c06fb_example


fprintf('c06fb example results\n\n');

% Hermitian sequence x, stored in Hermitian form.
n = 7;
x = [0.34907;  0.5489;   0.74776;   0.94459;
     1.1385;   1.3285;   1.5137];

% DFT of x
[xtrans, ifail] = c06fa(x);

% Display in full complex form
z = nag_herm2complex(xtrans);
disp('Discrete Fourier Transform of x:');
disp(transpose(z));

% Inverse DFT of xtrans
[xres] = nag_hermconj(xtrans);
[xres, ifail] = c06fb(xres);

 
fprintf('Original sequence as restored by inverse transform\n\n');
fprintf('       Original   Restored\n');
for j = 1:n
  fprintf('%3d   %7.4f    %7.4f\n',j, x(j),xres(j));
end
 


function [z] = nag_herm2complex(x);
  n = int64(size(x,1));
  z(1) = complex(x(1));
  for j = 2:floor((n-1)/2) + 1
    z(j) = x(j) + i*x(n-j+2);
    z(n-j+2) = x(j) - i*x(n-j+2);
  end
  if (mod(n,2)==0)
    z(n/2+1) = complex(x(n/2+1));
  end

function [xconj] = nag_hermconj(x);
  n = size(x,1);
  n2 = floor((n+4)/2);
  xconj = x;
  for j = n2:n
    xconj(j) = -x(j);
  end

c06fb example results

Discrete Fourier Transform of x:
   2.4836 + 0.0000i
  -0.2660 + 0.5309i
  -0.2577 + 0.2030i
  -0.2564 + 0.0581i
  -0.2564 - 0.0581i
  -0.2577 - 0.2030i
  -0.2660 - 0.5309i

Original sequence as restored by inverse transform

       Original   Restored
  1    0.3491     0.3491
  2    0.5489     0.5489
  3    0.7478     0.7478
  4    0.9446     0.9446
  5    1.1385     1.1385
  6    1.3285     1.3285
  7    1.5137     1.5137

PDF version (NAG web site, 64-bit version, 64-bit version)

Chapter Contents

Chapter Introduction

NAG Toolbox