LTFAT version 1.0 was released on June 18. 2011 after more than 7
years of development.

The Linear Time-Frequency Analysis Toolbox (LTFAT) is a free software
toolbox (GPLv3) written in the Matlab/Octave scripting language. It
comprises more than 200 different functions in the area of Fourier
analysis, signal processing and time-frequency analysis.

The toolbox can be downloaded from http://ltfat.sourceforge.net.

The toolbox can be used for both educational, research and
computational purposes. It has a backend implemented in C, which can
be compiled to speed up all computational intensive functions.

The following is a list of the current major functionality in LTFAT:

Fourier analysis:
* FFT for real valued signals (fftreal) and its inverse.
* 8 different discrete cosine and sine transforms.
* Next fast FFT size (modern nextpow2 replacement).
* Periodic, zero-delay filtering.
* Periodic, discrete function (chirp, heaviside, sinc etc.)
* 2 different classes of discrete Hermite functions.
* Periodic Gauss function.
* Long list of classic FIR window functions (Hann, Hamming, Blackman,
  iterated sine, Nuttall etc.),

Time-frequency analysis:
* The discrete Gabor transform (DGT) and its inverse.
* Wilson and windowed MDCT bases.
* Methods for constructing dual and tight windows (perfect and
  paraunitary filter prototypes).
* GUI (Matlab-only) to modify signals in the time-frequency domain.
* Spectrogram and reassigned spectrogram plots.
* Accurate computation of localized instantaneous frequency and group
  delay.
* Twisted convolution and discrete, symplectic Fourier transform.
* Zak transform and its inverse.
* TF-multiplier operators with adjoint and best approximation
  function.
* Spreading operators with inverse and adjoint.
* Reconstruction from the magnitude of the DGT.

Filterbanks:
* Uniform filterbanks and inverse.
* Non-uniform filterbanks and inverse.
* Methods for constructing dual and tight filterbanks (perfect reconstruction
  and paraunitary filterbanks).

Time-evolving TF-systems:
* Non-stationary Gabor systems (NSDGT) and inverse.
* Methods for constructing dual and tight NSDGTs.

Auditory functions:
* Perceptual frequency scales: Erb, Bark and Mel scales.
* Gammatone filters.
* Range compression (mu-law and A-law).

Signal processing:
* Levels of signals: RMS-norm, gain and crest factor.
* Ramping of signals based on FIR windows.
* Simple tools for working with coefficients (thresholding, N-term
  approx. etc)
* Group and elitist threshholding.
* Sparse regression in the Gabor and WMDCT domain.
* Uniform quantization.

and not forgetting:
* Demos demonstrating the use of the toolbox.
* Test signals: sounds, images and noise generators (white, pink,
  red/brown noise).


On behalf of the LTFAT developers,

Peter L. Soendergaard.
