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Quickly locate your Signal Components

AutoSignal gives researchers the power to rapidly find the components of complex signals that usually require extensive programming and mathematical routines. You get a vast array of spectral analysis procedures that will help you reach intelligent conclusions irrespective of the exact nature of the problem you are faced with. AutoSignal's built-in spectral analysis procedures include: FFT, AutoRegressive, Moving Average, ARMA, complex exponential modeling, minimum variance method, Eigen analysis frequency estimation and wavelets.

Identify frequency and power with Fourier Spectrum analysis

AutoSignal lets you see a complete picture of the frequency space using the library of six Fourier Spectrum methods with total flexibility. Solve the leakage problem found with standard FFT by using one of the 30 included data tapering windows. You can even make comparisons of performance of various data tapering windows in a single spectral graph. AutoSignal gives you access to the latest methodologies with techniques such as FFT Multitaper Spectrum analysis to help you better characterise the power in each signal. Easily handle your unevenly sampled data with Lomb-Scargle Fourier domain analysis with techniques that were originally developed by astrophysicists.

Effortlessly analyse non-stationary data with wavelets

Simultaneously find the time and frequency localisation components of a non-stationary periodic signal with Continuous Wavelet Spectrum analysis techniques. AutoSignal gives you a choice of three adjustable mother wavelets: Morlet, Paul and Gaussian Derivative - in both real and complex forms to optimise localisation results. You can also perform power analysis in either the time or the frequency range with specialised in-depth analysis techniques to evaluate the signal.

Isolate components by signal strength using eigendecomposition

In addition to FFT and wavelet spectral analysis techniques, you can select from linear and nonlinear methods that are right for your application. The eigendecomposition procedures enable you to visually select eigenmodes for signal-noise separation or component isolation. With AutoSignal, you can also recover signal components based on power - the component may be sinusoidal, a square wave, a sawtooth or anharmonic pattern. You can confirm the presence of white noise or isolate red noise by reconstructing only the noise eigenmodes.

Precisely estimate with advanced parametric modelling

With AutoSignal, you get state-of-the-art parametric nonlinear modelling for sinusoid and damped sinusoid models. Nonlinear optimisation is also available as an independent procedure, or as an adjunct to each of the spectral algorithms. It includes robust maximum-likeihood optimisations as well as automatic parameter constraints. AutoRegressive linear methods offer robust performance that can quickly handle smaller data sets that FFT cannot accurately analyse.

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 bins - 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 and Loess 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 using 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 visualisation tool, AutoSignal automatically plots your peaks, contours or 3D surfaces - so you don't have to perform additional steps to see your results. You can change any algorithm or analysis option through the user interface and see instant results. Isolate components of a signal graphically using eigendecomposition to display and select eigen components in order to find very low frequency oscillatory components or identify paired eigenmodes producing a specific oscillation. Then, analyse 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 title, fonts, colors, prints, scaling, axis scale, labels, grid and plot types.

Save precious research time with the production facility

What once took hours now takes seconds - with only a few mouse clicks. It's so easy - even novice users can learn how to use AutoSignal in no time. Every procedure is automated. For even more muscle, streamline your work with the production facility to automate batch analysis and reporting. With an easy-to-use dialog, set up your batch import and export options. Link directly to your hardware to analyse and report options. Link directly to your hardware to analyse and report on the fly. Already have your data in Microsoft^® Excel? No problem. Process up to 255 Excel worksheets at once. Create RTF reports with numerical summaries that include publication-quality graphs or export the data to a new Excel workbook. With AutoSignal, it's so simple!