Signal Processing
If X is a vector, `detrend (X, P)' removes the best fit of a polynomial
of order P from the data X.
Compute the FFT of A using subroutines from FFTW.
Manage FFTW wisdom data.
Compute the inverse FFT of A using subroutines from FFTW.
Compute the two dimensional FFT of A using subroutines from FFTW.
Compute the inverse two dimensional FFT of A using subroutines from
FFTW.
Compute the N dimensional FFT of A using subroutines from FFTW.
Compute the inverse N dimensional FFT of A using subroutines from FFTW.
Return the convolution of the vectors A and B, as a vector with length
equal to the `length (a) + length (b) - 1'.
With two arguments, `fftfilt' filters X with the FIR filter B using the
FFT.
Return the solution to the following linear, time-invariant difference
equation:
Apply the 2-D FIR filter B to X.
Return the complex frequency response H of the rational IIR filter
whose numerator and denominator coefficients are B and A, respectively.
Plot the pass band, stop band and phase response of H.
Return sin(pi*x)/(pi*x).
Unwrap radian phases by adding multiples of 2*pi as appropriate to
remove jumps greater than TOL.
Fit an ARCH regression model to the time series Y using the scoring
algorithm in Engle's original ARCH paper.
Simulate an ARCH sequence of length T with AR coefficients B and CH
coefficients A.
For a linear regression model
Return a simulation of the ARMA model
Return the autocorrelations from lag 0 to H of vector X.
Return the autocovariances from lag 0 to H of vector X.
Given a time series (vector) Y, return a matrix with ones in the first
column and the first K lagged values of Y in the other columns.
Return the filter coefficients of a Bartlett (triangular) window of
length M.
Return the filter coefficients of a Blackman window of length M.
Return the estimator D for the differencing parameter of an integrated
time series.
Perform one step of the Durbin-Levinson algorithm.
Perform a shift of the vector V, for use with the `fft' and `ifft'
functions, in order the move the frequency 0 to the center of the
vector or matrix.
Undo the action of the `fftshift' function.
Compute the fractional differences (1-L)^d x where L denotes the
lag-operator and d is greater than -1.
Return the filter coefficients of a Hamming window of length M.
Return the filter coefficients of a Hanning window of length M.
Estimate the Hurst parameter of sample X via the rescaled range
statistic.
Piecewise Cubic Hermite interpolating polynomial.
For a data matrix X from a sample of size N, return the periodogram.
Rectangular lag window.
Rectangular spectral window.
Return a sinetone of frequency FREQ with length of SEC seconds at
sampling rate RATE and with amplitude AMPL.
Return an M-element vector with I-th element given by `sin (2 * pi *
(I+D-1) / N)'.
Return the spectral density estimator given a vector of autocovariances
C, window name WIN, and bandwidth, B.
Return the spectral density estimator given a data vector X, window
name WIN, and bandwidth, B.
Return Spencer's 15 point moving average of every single column of X.
Compute the short-term Fourier transform of the vector X with NUM_COEF
coefficients by applying a window of WIN_SIZE data points and an
increment of INC points.
Compute a signal from its short-time Fourier transform Y and a
3-element vector C specifying window size, increment, and window type.
Triangular lag window.
Triangular spectral window.
Fit an AR (p)-model with Yule-Walker estimates given a vector C of
autocovariances `[gamma_0, .