smart_signal_processing

Description:

smart signal processing

Smart Signal Processing #
What the package can do for you #
This package provides frequently used functions for signal processing:

Computes mean values, variance, standard deviation.
Applies windowing (apodization functions) with exponential or Gaussian shapes to an array
Applies the Fast Fourier Transform to an array.
Calculates the power or magnitude of a complex-valued array.
Phase-shifts (rotates in the complex plane) a complex-valued array.

Example #


The provided example can be directly executed via https://smart.specpad.bplaced.net/smart_signal_processing/example.html.


Or, download the package and execute the file example/example.html in your browser.


The major API functionalities #

classes Sigma, BaseLine, WinFunc,FFT, Phase.

Examples:


Multiplication with an exponential:
WinFunc.expMult(array, decayFactor, false, "0");


Compute Fourier Transform:
FFT.transform(reals, imags);


Compute magnitude:
Phase.magnitude(reals, imags, true)


Compute variance in a region:
Sigma.variance(array, ixstart, ixend)


Related packages #
smart_arrays_base: Basic functions for 1D and 2D arrays
smart_arrays_numerics: Numerics with 1D and 2D arrays
smart_arrays_compress: Compress 1D and 2D arrays to a smaller size.
smart_arrays_sample_data: Computes 1D and 2D arrays containing sample data.
smart_arrays_dbstore: Store 1D and 2D arrays along with metadata on the local device.
smart_arrays_plot_polyline: Plot 1D arrays as polyline along with axes and more.
smart_arrays_peaks: Detect peaks in 1D and 2D arrays.
smart_arrays_contour_finder: Contours the three-dimensional surface represented by the values f(x,y) of a matrix.
smart_arrays_lmfit: Fits (x, y) data given as arrays to a specified model function using the Levenberg-Marquardt algorithm.
smart_lorentz-gauss: Compute Lorentz-Gauss (pseudo-Voigt) line shapes.
smart_dialogs: Easy-to-use dialogs in Web applications