AutoSignal 1.7
Parametric modeling
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 analyse.
Easily smooth and process your signals
AutoSignal gives researchers the power to rapidly find components of complex signals that normally require Only AutoSignal offers so many different user-friendly methods to manipulate signal data. You can inspect your data stream in the Fourier domain and zero higher frequency points - and see your results immediately in the time domain. This smoothing technique allows for superb noise reduction while maintaining the integrity of the original data stream. AutoSignal also includes eigendecomposition, wavelet, Savitzky-Golay, Loess and detrending for smoothing and denoising. Isolate components and detect signals with powerful filtering and reconstruction techniques with Fourier, eigendecomposition and wavelet methods. For instance, isolate components that appear and disappear with wavelet filtering and reconstruction. Recover the true signal that would have been measured using an ideal sensing system with Gaussian and exponential deconvolution.
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.