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-
- _D_i_s_c_r_e_t_e _F_o_u_r_i_e_r _T_r_a_n_s_f_o_r_m
-
- fft(z, inverse=F)
- mvfft(z, inverse=F)
-
- _A_r_g_u_m_e_n_t_s:
-
- z : a real or complex value array containing the
- values to be transformed
-
- inverse : if TRUE, the inverse transform is computed
- (the inverse has a + in the exponent of e and
- divides the values by 1/length(x) before
- transforming).
-
- _V_a_l_u_e:
-
- When z is a vector, the value computed and returned by
- fft is the univariate Fourier transform of the sequence
- of values in z. When z contains an array, fft computes
- and returns the multivariate (spatial) transform.
-
- By contrast, mvfft takes a real or complex matrix as
- argument, and returns a similar shaped matrix, but with
- each column replaced by its discrete Fourier transform.
- This is useful for analysing vector-valued series.
-
- The FFT is fastest when the length of of the series
- being transformed is highly composite (i.e. has many
- factors). If this is not the case, the transform may
- take a long time to compute and will use a large amount
- of memory.
-
- _R_e_f_e_r_e_n_c_e_s:
-
- Singleton, R. C. (1979). Mixed Radix Fast Fourier
- Transforms, in Programs for Digital Signal Processing,
- IEEE Digital Signal Processing Committee eds. IEEE
- Press.
-
- _S_e_e _A_l_s_o:
-
- convolve, nextn.
-
- _E_x_a_m_p_l_e_s:
-
- plot(fft(c(9:0,0:13, numeric(301))),type='l')
- periodogram <- function(x) { ##-- simple periodogram of x[]
- n <- length(x)
- Mod(fft(unclass(x)))[1:(n%/%2 + 1)]^2 / (2*pi*n)
- }
- data(sunspots)
- plot(10*log10(periodogram(sunspots)),type='b', col='blue')
-
-