Signal Processing

The toolbox contains numerous algorithms which implements various kind of time-frequency analysis with a special emphasis on quadratic energy distributions of the Cohen and affine classes, along with their version enhanced by the reassignment method. The toolbox also includes signal generation procedures, processing/post-processing routines (with display utilities) and a number of demonstrations.

Linear SystemInversion Toolbox 

The Linear System Inversion Toolbox is a Scilab toolbox for stable inversion of linear time-invariant systems. The inverse calculations are optimal in the sense that a certain norm criterion is minimized. Decision delays are also implemented for some cases.

Empirical Mode Decomposition (EMD) Toolbox 

Toolbox for Empirical Mode Decomposition of 1-D, 2-D and higher dimensional signals.

Using the EMD method, any complicated data set can be decomposed into a finite and often small number of components, which is a collection of intrinsic mode functions (IMF). An IMF represents a generally simple oscillatory mode as a counterpart to the simple harmonic function. By definition, an IMF is any function with the same number of extrema and zero crossings, with its envelopes being symmetric with respect to zero. The definition of an IMF guarantees a well-behaved Hilbert transform of the IMF. This decomposition method operating in the time domain is adaptive and highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it can be applied to nonlinear and nonstationary processes.