AutoSignal - Perform Complex Signal Analysis Software
Perform Complex Signal Analysis with a Mouse Click, No Programming Required! AutoSignal is the first and only program that completely automates the process of analyzing signals. Save precious time by eliminating the programming time normally required for performing sophisticated signal analysis. AutoSignal takes full advantage of its graphical user intuitive interface to simplify every aspect of operation, from data import to output of results.
Choose your analysis techniques from the menu or toolbar. Select the algorithm and options from the interface. You get immediate visual feedback with 2D or 3D graphs of your signal analysis plus numeric summaries for reports.
AutoSignal gives researchers the power to rapidly find components of complex signals that normally require extensive programming and mathematical routines. AutoSignal provides a vast array of spectral analysis procedures to help you make intelligent conclusions for any application. Built-in spectral analysis procedures include:
- Moving Average
- Complex exponential modeling
- Minimum variance methods
- Eigen analysis frequency estimation and Wavelets
Precisely estimate with advanced parametric modeling
With AutoSignal, you get state-of-the-art parametric nonlinear modeling for sinusoid and damped sinusoid models. Non-linear optimization is also available as an independent procedure or as an adjunct to each of the spectral algorithms.
It includes robust maximum-likelihood optimizations as well as automatic parameter constraints. AutoRegressive linear models offer robust models that can quickly handle smaller data sets that FFT cannot accurately analyze.
Graphically review signal analysis results
As a powerful visualization tool, AutoSignal automatically plots your peaks, contours or 3D surfaces – so you don’t have to perform additional steps to see your results. Change any algorithm or analysis option on the fly through the user interface and see instant results. Isolate components of a signal graphically using eigen decomposition to display and select eigen components in order to find very low frequency oscillatory components or identify paired eigen modes producing a specific oscillation.
Analyze your results with residual and root plots and show statistical significance and probability limits on your output graphs. Clearly present your results with control over titles, fonts, colors, points, scaling, axis scale, labels, grid and plot types.