smart_signal_processing 2.0.7

Provides useful functions for signal processing such as Fast Fourier Transform, windowing (apodization), variance/standard deviation and others.

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)

Detailed API

Please view the detailed API documentation in the API reference of this package (sidebar at the right of this page).

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_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_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