Signal processing tools, including filtering, windowing and display functions.

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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.

Compute the Meyer wavelet auxiliary function.

Compute the Morlet wavelet.

Compute the Mexican hat wavelet.

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.

Evaluate a train of sigmoid functions at T.

Generate a spectrogram for the signal X.

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

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

Forward and reverse filter the signal.

Set initial condition vector for filter function The vector zf has the same values that would be obtained from function filter given past inputs x and outputs y

Apply a median filter of length N to the signal X.

Calculate moving RMS value of the signal in 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.

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.

Compute peak full-width at half maximum (FWHM) or at another level of peak maximum for vector or matrix data Y, optionally sampled as y(x).

Compute the group delay of a filter.

Generate impulse-response characteristics of the filter.

Plot the poles and zeros.

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

b = polystab(a)

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

Compute the partial fraction expansion (PFE) 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.

Convert 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.

Return bessel analog filter prototype.

Generate a bessel filter.

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

Design lowpass analog Butterworth filter.

Generate a butterworth filter.

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

Returns the value of the nth-order Chebyshev polynomial calculated at the point x.

Design lowpass analog Chebyshev type I filter.

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

Design lowpass analog Chebyshev type II filter.

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.

Generate an Elliptic or Cauer filter (discrete and contnuious).

Design lowpass analog elliptic filter.

usage: [n,wp] = ellipord(wp,ws, rp,rs)

IIR Low Pass Filter to Multiband Filter Transformation

Converts analog filter with coefficients B and A to digital, conserving impulse response.

Converts digital filter with coefficients B and A to analog, conserving impulse response.

usage: [Zz, Zp, Zg] = ncauer(Rp, Rs, n)

Return coefficients for an IIR notch-filter with one or more filter frequencies and according (very narrow) bandwidths to be used with `filter' or `filtfilt'.

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

Constrained L2 bandpass FIR filter design.

Produce an order N FIR filter with the given frequency cutoff W, returning the N+1 filter coefficients in B.

Produce an order N FIR filter with arbitrary frequency response M over frequency bands F, returning the N+1 filter coefficients in B.

FIR filter design using least squares method.

Return the parameters needed to produce a filter of the desired specification from a Kaiser window.

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).

Reorder the elements of the vector X in bit-reversed order.

Return 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.

Compute the discrete cosine transform of X.

Return the DCT transformation matrix of size N-by-N.

Compute the 2-D discrete cosine transform of matrix X.

Compute the N-by-N Fourier transformation matrix.

Reorder the elements of the vector X in digit-reversed order.

Computes the type I discrete sine transform of X.

Discrete wavelet transform (1D).

Calculate the Fast Hartley Transform of real input D.

Compute the Walsh-Hadamard transform of X using the Fast Walsh-Hadamard Transform (FWHT) algorithm.

Analytic extension of real valued signal.

Compute the inverse discrete cosine transform of X.

Compute the inverse 2-D discrete cosine transform of matrix X.

Computes the inverse type I discrete sine transform of Y.

Calculate the inverse Fast Hartley Transform of real input D.

Compute the inverse Walsh-Hadamard transform of X using the Fast Walsh-Hadamard Transform (FWHT) algorithm.

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

Calculate the power spectrum of the autoregressive model

Usage: [Pxx,freq] = cohere(x,y,Nfft,Fs,window,overlap,range,plot_type,detrend)

Estimate cross power spectrum of data X and Y by the Welch (1967) periodogram/FFT method.

Usage: [Pxx,freq] = csd(x,y,Nfft,Fs,window,overlap,range,plot_type,detrend)

Usage: [Pxx,freq] = tfe(x,y,Nfft,Fs,window,overlap,range,plot_type,detrend)

Estimate transfer function of system with input X and output Y.

Estimate (mean square) coherence of signals X and Y.

usage: [psd,f_out] = pburg(x,poles,freq,Fs,range,method,plot_type,criterion)

USAGE: [spectra,freq] = pwelch(x,window,overlap,Nfft,Fs, range,plot_type,detrend,sloppy) Estimate power spectral density of data "x" by the Welch (1967) period

usage: [psd,f_out] = pyulear(x,poles,freq,Fs,range,method,plot_type)

Estimates the cross-correlation.

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.

Compute the modified Bartlett-Hann window of length L.

Compute the Blackman-Harris window.

Compute the Blackman-Nuttall window.

Compute the Bohman window of length L.

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

Returns the filter coefficients of the L-point Dolph-Chebyshev window with AT dB of attenuation in the stop-band of the corresponding Fourier transform.

Return the window f(w):

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

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

w = hann(n) see hanning

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

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

Compute the Parzen window of length L.

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

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

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

Return as column-vector W, the coefficients of the L-point Ultraspherical window, where MU controls the window's Fourier transform's side-lobe to side-lobe ratio, and the third given parameter control

Returns a row vector containing a Welch window, given by W(n)=1-(n/N-1)^2, n=[0,1, ...

Create an N-point window from the function F.

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

Fit an AR (P)-model with Yule-Walker estimates.

usage: [B,A] = invfreq(H,F,nB,nA) [B,A] = invfreq(H,F,nB,nA,W) [B,A] = invfreq(H,F,nB,nA,W,[],[],plane) [B,A] = invfreq(H,F,nB,nA,W,iter,tol,plane)

Usage: [B,A] = invfreqs(H,F,nB,nA) [B,A] = invfreqs(H,F,nB,nA,W) [B,A] = invfreqs(H,F,nB,nA,W,iter,tol,'trace')

usage: [B,A] = invfreqz(H,F,nB,nA) [B,A] = invfreqz(H,F,nB,nA,W) [B,A] = invfreqz(H,F,nB,nA,W,iter,tol,'trace')

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

Creates a vectorized function based on data samples using interpolation.

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, FIR filtering, and downsample.

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

Buffer a signal into a data frame.

Calculate boundary indexes of clusters of 1's.

Finds peaks on DATA.

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

Compute the generalized Marcum Q function of order M with noncentrality parameter A and argument B.

Calcuates the primitive of a function.

Calculate the x(t) reconstructed from samples x[n] sampled at a rate 1/T samples per unit time.

Implements a multisignal Schmitt trigger with levels LVL.

Upsamples a vector interleaving given values or copies of the vector elements.

1-D or 2-D convolution.

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.

Estimates the points at which a given waveform y=y(x) crosses the x-axis using linear interpolation.

Package: signal