Produce an order n FIR filter with the given frequency cutoff, returning the n+1 filter coefficients in b.

Produce an FIR filter of order n with arbitrary frequency response, returning the n+1 filter coefficients in b.

filter design using least squares method.

Returns the parameters needed for fir1 to produce a filter of the

Computes a finite impulse response (FIR) filter for use with a quasi-perfect reconstruction polyphase-network filter bank.

Parks-McClellan optimal FIR filter design.

Computes the filter coefficients for all Savitzsky-Golay smoothing filters of order p for length n (odd).

Compute the s-plane frequency response of the IIR filter B(s)/A(s) as H = polyval(B,j*W)./polyval(A,j*W).

Plot the amplitude and phase of the vector H.

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.

Compute the group delay of a filter.

Generate impulse-response characteristics of the filter.

Plot the poles and zeros.

converts the autocorrelation sequence into an AR polynomial

converts the autocorrelation function into reflection coefficients

If A is a column vector and X is a column vector of length N, then

converts an AR polynomial into an autocorrelation sequence

converts AR-polynomial into reflection coefficients

Stabalize the polynomial transfer function by replacing all roots outside the unit circle with their reflection inside the unit circle.

converts reflection coefficients to autocorrelation sequence

converts reflection coefficients into an AR-polynomial

Compute the partial fraction expansion (PFE) of filter H(z) = B(z)/A(z).

Compute the partial fraction expansion of filter H(z) = B(z)/A(z).

Convert series second-order sections to direct form H(z) = B(z)/A(z).

Convert series second-order sections to zeros, poles, and gains (pole residues).

Conversion from transfer function to state-space.

Converts a state space representation to a set of poles and zeros; K is a gain associated with the zeros.

Convert direct-form filter coefficients to series second-order sections.

Conversion from transfer function to state-space.

Converts transfer functions to poles-and-zero representations.

Convert filter poles and zeros to second-order sections.

Conversion from zero / pole to state space.

Converts zeros / poles to a transfer function.

With two arguments, `fftfilt' filters X with the FIR filter B using the FFT.

Forward and reverse filter the signal.

Set initial condition vector for filter function

Compute the fractional differences (1-L)^d x where L denotes the lag-operator and d is greater than -1.

Apply a median filter of length n to the signal x.

Smooth the data in x with a Savitsky-Golay smoothing filter of polynomial order p and length n, n odd, n > p.

Second order section IIR filtering of X.

Return Spencer's 15 point moving average of every single column of X.

Transform a s-plane filter specification into a z-plane specification.

Generate a butterworth filter.

Compute butterworth filter order and cutoff for the desired response characteristics.

Compute chebyshev type I filter order and cutoff for the desired response characteristics.

Compute chebyshev type II filter order and cutoff for the desired response characteristics.

Generate an Chebyshev type I filter with Rp dB of pass band ripple.

Generate an Chebyshev type II filter with Rs dB of stop band attenuation.

N-ellip 0.2.1

Calculate the order for the elliptic filter (discrete)

Analog prototype for Cauer filter.

Transform band edges of a generic lowpass filter (cutoff at W=1) represented in splane zero-pole-gain form.

Fit an AR (p)-model with Yule-Walker estimates given a vector C of autocovariances `[gamma_0, ..., gamma_p]'.

Calculate the power spectrum of the autoregressive model

coherence of signals "x" and "y".

Estimate cross power spectrum of data "x" and "y" by the Welch (1967) periodogram/FFT method.

Estimate cross power spectrum of data "x" and "y" by the Welch (1967) periodogram/FFT method.

coherence of signals "x" and "y".

Calculate Burg maximum-entropy power spectral density.

pwelch(x,window,overlap,Nfft,Fs,

Calculates a Yule-Walker autoregressive (all-pole) model of the data "x" and computes the power spectrum of the model.

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.

Estimate transfer function of system with input "x" and output "y".

Estimate transfer function of system with input "x" and output "y".

Compute correlation R_xy of X and Y for various lags k:

Compute the 2D cross-correlation of matrices A and B.

Compute covariance at various lags [=correlation(x-mean(x),y-mean(y))].

Plot the power spectrum of the given ARMA model.

Downsample the signal x by a factor of q, using an order n filter of ftype 'fir' or 'iir'.

Downsample the signal, selecting every nth element.

Upsample the signal x by a factor of q, using an order 2*q*n+1 FIR filter.

Change the sample rate of X by a factor of P/Q.

Upsample, filter and downsample a signal.

Upsample the signal, inserting n-1 zeros between every element.

Buffer a signal into a data frame.

Evaluate a chirp signal at time t.

Compute the Complex Morlet wavelet.

Compute the dirichlet function.

Return the Gaussian modulated sinusoidal pulse.

Return the gaussian monopulse.

Estimate the Hurst parameter of sample X via the rescaled range statistic.

Compute the Mexican hat wavelet.

Compute the Meyer wavelet auxiliary function.

Compute the Morlet wavelet.

For a data matrix X from a sample of size N, return the periodogram.

Generate the signal y=sum(func(t+d,...)) for each d.

Generate a rectangular pulse over the interval [-w/2,w/2), sampled at times t.

Generates a sawtooth wave of period `2 * pi' with limits `+1/-1' for the elements of T.

Compute the Complex Shannon wavelet.

Return sin(pi*x)/(pi*x).

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)'.

Generate a spectrogram for the signal.

Generate a square wave of period 2 pi with limits +1/-1.

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.

Generate a triangular pulse over the interval [-w/2,w/2), sampled at times t.

Calculate coefficients of an autoregressive (AR) model of complex data "x" using the whitening lattice-filter method of Burg (1968).

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

fits an AR (p)-model with Yule-Walker estimates.

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 estimator D for the differencing parameter of an integrated time series.

Perform one step of the Durbin-Levinson algorithm.

Fit filter B(z)/A(z) or B(s)/A(s) to complex frequency response at frequency points F.

Fit filter B(s)/A(s)to the complex frequency response H at frequency points F.

Fit filter B(z)/A(z)to the complex frequency response H at frequency points F.

Use the Durbin-Levinson algorithm to solve: toeplitz(acf(1:p)) * x = -acf(2:p+1).

Linear prediction coefficients

Reorder x in the bit reversed order See also: fft,ifft.

Returns the complex cepstrum of the vector x.

Split the vector z into its complex (ZC) and real (ZR) elements, eliminating one of each complex-conjugate pair.

Chirp z-transform.

Computes the discrete cosine transform of x.

Computes the 2-D discrete cosine transform of matrix x

Return the DCT transformation matrix of size n x n.

If N is a scalar, produces a N-by-N matrix D such that the Fourier transform of a column vector of length N is given by `dftmtx(N) * x' and the inverse Fourier transform is given by `inv(dftmtx(N)) * x'.

Computes the type I discrete sine transform of X.

Comupte de discrete wavelet transform of x with one level.

The function fht calculates Fast Hartley Transform where D is the real input vector (matrix), and M is the real-transform vector.

Analytic extension of real valued signal

Computes the inverse discrete cosine transform of x.

Computes the inverse 2-D discrete cosine transform of matrix x

Computes the inverse type I discrete sine transform of Y.

The function ifht calculates Fast Hartley Transform where D is the real input vector (matrix), and M is the real-transform vector.

Produce the cepstrum of the signal x, and if desired, the minimum phase reconstruction of the signal x.

Buffer a signal into a data frame.

Shift the series X by a (possibly fractional) number of samples D.

Extract the elements of x of size l from the center, the right or the left.

Reverse the order of the element of the vector x.

Compute the modified Bartlett-Hann window of lenght L.

Return the filter coefficients of a Bartlett (triangular) window of length M.

Return the filter coefficients of a Blackman window of length M.

Compute the Blackman-Harris window.

Compute the Blackman-Nuttall window.

Compute the Bohman window of lenght L.

Returns the filter coefficients of a rectangular window of length n.

Returns the filter coefficients of the n-point Dolph-Chebyshev window

Return the window f(w):

Generate an n-point gaussian convolution window of the given width.

Generate an n-point gaussian window of the given width.

Return the filter coefficients of a Hamming window of length M.

see hanning

Return the filter coefficients of a Hanning window of length M.

Returns the filter coefficients of the n-point Kaiser window with parameter beta.

Compute the Blackman-Harris window defined by Nuttall of length L.

Compute the Parzen window of lenght L.

Rectangular lag window.

Rectangular spectral window.

Return the filter coefficients of a rectangle window of length N.

Returns the filter coefficients of a triangular window of length n.

Triangular lag window.

Triangular spectral window.

Return the filter coefficients of a Tukey window (also known as the cosine-tapered window) of length M.

Compute the Welch window, given by w(n) = 1 - ((n-L/2)/(L/2))^2, n=0,1, ... L-1 See also: blackman, kaiser.

Create a N-point windowing from the function F.