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A timely breakthrough in cutting-edge signal analysis
Riassunto
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. See the Screenshot
Quickly locate your signal components
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:
• FFT
• AutoRegressive
• Moving Average
• ARMA
• 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 analyse. See the Screenshot
Easily smooth and process your signals
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.
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 Multi-taper 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.
See the Screenshot
Effortlessly analyze 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 non-linear 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. See the Screenshot
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 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!
Analisi statistica
Analisi varianza
Varianza statistica
Analisi regressione
Statistica modello esponenziale
Statistica modello non lineare
Statistica modello lineare
Analisi segnale
Identificazione segnale
The Automatic choice for state - of - art signal analysis
Unlike any other tools, AutoSignal has an easy-to-use automated interface that requires no programming to perform signal analysis. AutoSignal provides sophisticated tools for researchers to identify the underlying physical process that produces a given waveform. Every step of your analysis is automated. AutoSignal saves you the time normally required in performing calculations or programming. Filter, process and analyze your complex signals with interactive graphics and detailed numerical summaries.
AutoSignalTM is a powerful solution that solves real world problems - fast !
• Communication signal identification and analysis
• Signal interference monitoring
• Control systems analysis
• Audio system analysis
• Voice recognition and speech processing
• Signature analysis
• Vibration analysis
• Acoustical analysis
• Radar signal analysis
• Analog circuit testing
• Signal detectors
• Sea spectra study
• Astrophysics
AutosignalTM provides a wide selection of state-of-the-art methods, including : spectral analysis, filtration and data reconstruction via FFT, parametric, eigen and wavelet methods. Time domain algorithms for smoothing, interpolating and prediction, can be used. Furthermore, AutoSignal can be used in a classroom or lab to help students apply the theories they've learned in their classes such as signal theory or physics.
Interface
• Full 32-bit performance
• Toolbars and menu-driven for all functionality
• No programming of procedures, algorithms or graphing
• Advanced on-line help system
Non-Parametric Spectral Analysis
• AR spectral methods offer accurate frequency estimation with short data records
• AR spectrum methods: AR spectrum, AR with order exploration, AR with algorithm comparison
• 14 AR algorithms: autocorrelation method, maximum entropy method (Burg), least-squares normal equations, least-squares covariance models and modified covariance models, singular value decomposition methods
• Model order selection and order exploration
• Moving average spectrum
• ARMA spectrum
• Prony Spectrum offers fitting of damped sine and damped exponential that occur in multi-component exponential decays
• Minimum Variance Spectrum
Eigen Analysis Spectrum
• Eigen Analysis Spectrum provides accurate and robust spectral procedures for estimating harmonic frequencies
• Provides excellent signal-noise separation
• Graphically select signal and noise sub-space; also available in certain parametric procedures
Data Processing
• Non-Linear Optimization offers parametric refinement of spectral estimates: least-squares, maximum likelihood
• Fourier Interpolation
• Fourier Upsampling
• Parametric Interpolation and Prediction
• Graphically inspect the autocorrelation series
• Detrend: Constant, Linear, Quadratic, Cubic, Logarithmic, Exponential, Power, Hyperbolic
• Difference the data with adjustable order and lag, compute various cumulatives, and normalize for unit area, unit power, unit standard deviation, and zero mean
• Add or subtract a reference signal
• Compare imported reference signals
• Gaussian deconvolution or exponential deconvolution to remove instrument response smearing
• Find long-term "memory effects" in flat frequency response signals with Fractal Dimension option
Numeric Review
• Full component numeric summary report include: procedure, algorithm, listing of interpolated spectral peaks, frequency analysis and linear least-squares fit summary
• List data offers extended data summary with results from each of the procedure such as frequency, magnitude, phase and power spectral density
• Goodness of fit statistics: r2, degrees of freedom adjusted r2, fit standard error, F-statistic
• Evaluation option with automated table generation, includes function, derivatives, roots and cumulative volume; X values can be generated or imported from file
Output and Export
• Publication-quality printed graphs
• Image formats include bitmaps, metafiles, enhanced metafiles and device-independent bitmaps
• File formats include ASCII, Excel, Lotus, SYSTAT, SPSS
• Export numerical summaries and graphs to MS Word RTF documents
Data Input
• Up to 65,536 points in data table
• Over 65.4 million points can be filtered into table using decimation import filter
• ASCII (Single, X-Y, and Multi-column)
• Excel (Excel 97, Excel 95, v5, v4, v3)
• Lotus 123 (WK4, WK3, WK1)
• Quattro Pro (WB2, WB1)
• SigmaPlot (JPG, SPW, SP5)
• SPSS (SAV v7.5, v8 and v9)
• SYSTAT (SYD v8)
• Waveform (WAV MS PCM 8, 16, 32 bit)
• DIF (Single, X-Y, and Multi-column)
• dBase (DBF III+, IV)
• Import Preview graphs prospective data
• Separate append options that automatically averages replicates
Fourier Spectral Analysis
• Procedures: Fourier Spectrum, Fourier Spectrum with Data Window, Fourier Spectrum with Data Window Comparison *, Fourier Spectrum of Segmented Data, Fourier Multitaper Spectra, Fourier Spectrum of Unevenly Sampled Data (Lomb-Scargle)
• Transforms: FFT Radix2, Prime Facto, Mixed Radix, Chirp-Z, Best Exact-N
• Zero pad
• 30 tapering windows:
• Fixed: none, Welch, Bisquare, Bartlett, cs2 Hanning, Tukey-Hanning, cs2 Hamming, Bartlett Mod, cs3 Nuttall C3, cs3 Blackman, cs3 Blackman-Harris 3, cs3 Nuttall C1, cs3 Blackman Exact, cs3 Blackman-Harris min, cs3 Nuttall min, cs4 Nuttall C5, cs4 Blackman-Harris 4, cs4 Nuttall C3, cs4 Nuttall C1, cs4 Blackman-Harris min, cs4 Nuttall min
Adjustable: Beta, csx max Roll-off, Kaiser-Bessel, VanderMaas, Chebyshev, Chebyshev Appr, Slepian DPSS, Gaussian, Tapered-Cosine
• Compare up to 4 tapering windows simultaneously
• Measure data window properties: mainlobe, sidelobe, roll-off
Time-Frequency Spectral Analysis
• Short-Time Fourier Transform Spectrum uses a series of segmented and overlapped FFTs to find Fourier spectral information for non-stationary data
• Continuous Wavelet Spectrum multi-resolution time-frequency techniques: 3D surface, contour, power integration across time or frequency
• Wavelet spectra can be generated with up to 100 linear or logarithmic frequencies
• Adjustable mother wavelets: Morlet, Paul, Gaussian Derivative
• Zero padding available
• Full critical significance limits available as 3D gradients
• Graphical rendering of cone of influence
• Automated power analysis by integrating interpolated wavelet spectrum surface
Filtering and Reconstruction
• Fourier Smoothing and Denoising: frequency or signal threshold filtration
• Eigen decomposition Smoothing and Denoising: signal strength threshold filtration
• Wavelet Smoothing and Denoising: thresholds in the time-frequency domain for non-stationary data.
• Fourier Filtering and Reconstruction: Fourier domain filtering and component isolation procedure
• Eigen decomposition Filtering and Reconstruction: isolates individual oscillatory components in signals
• Wavelet Filtering and Reconstruction: isolates in the time-frequency domain
• Savitzky-Golay Smoothing filter: includes smoothing to 1st through 4th derivative
• Spline Estimations: cubic, cubic constrained, smoothing cubic, B-spline, B-Spline Fix knots, B-spline Optimal knots, NURBS
• Adjustable order Loess with tricube and Gaussian weighting
Significance Levels
• Unique Peak-based critical limit levels to ascertain the significance of the spectral components
• Critical limits plotted are: 50%, 90%, 95%, 99%, 99.9% (uses color gradients for wavelets)
• Peak-type critical limits are based on Monte Carlo trials with algorithms exactly as implemented
• Can specify AR-1 red-noise background spectrum option
Production Facility
• Batch process large numbers of data sets in an unattended procedure
• Import up to 64,515 data sets from Excel 95/97 with up to 255 worksheets and multiple columns per worksheet
• Acquire data using simple DLL interface
• Automatically export numerical summaries and/or graphs to MS Word RTF documents
• Automatically export results of analysis to an Excel 95/97 file
Graphs
• Customization: Titles, axis labels, font size, font selection, grid, color schemes, point formats, axis scaling, log axis scaling, toggle data, reference data and function label display, modify contour and mesh properties.
• Save and import Views for standardized layouts.
• 3D Graph View: View angles, size in frame, illumination angular shifts, perspectives, backplanes, add contour plots.
• 3D Graph Types: Wire frame, mesh plot, 15 gradient plots, 4 shaded plots.
• Gradient and shaded plots use up to 48 colors.
• Plot formats: Real, Imaginary, Magnitude, Maginitude2, Phase, Mag/Phase (dual plot), Amplitude, Ampl/Phase (dual plot), dB, dB Norm, PSD SSA, PSD MSA, PSD TISA, Variance, Lomb, Prony ESD, Min Variance spectrum, MUSIC eigenvector, Wavelet spectrum.
Graphical Review
• Spectral peaks are identified graphically; select the number of peaks to detect.
• Display maxima with spectral peak labels: frequencies, spectral magnitudes, both frequencies and spectral magnitudes, none.
• Statistical feedback: set confidence/prediction intervals, show confidence/prediction intervals, error bars, critical limits, display residuals, display residuals as % of Y, residuals as fraction of SE, display residuals distribution, display delta SNP (stabilized normal probability) plot.
• 3D Graph animation.
• Intellimouse rotation of 3D view angles.
• Mesh resolution up to 300 x 300.
• View residuals, plot roots and plot AR selection criteria.
FFT Application Gallery: Identify frequency and power with Fourier Spectrum analysis
See a complete picture of the frequency space utilizing the library of six Fourier Spectrum methods with total flexibility. Solve the leakage problem found with standard FFT methods by using one of the 30 data tapering windows included. You have access to the latest methodologies with techniques such as FFT Multi-taper Spectrum analysis to help you better characterize the power in each signal. Easily handle unevenly sampled data with Lomb-Scargle Periodogram Fourier domain analysis with techniques that were originally developed by astrophysicists.
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Wavelet Application Gallery: Effortlessly analyze non-stationary data with Wavelets
Easily find the time and frequency localization components simultaneously of a non-stationary periodic signal with Continuous Wavelet Spectrum analysis techniques. Choose from three adjustable mother wavelets (Morlet, Paul and Gaussian Derivative) in both real and complex forms to optimize localization results. Perform power analysis in either time or frequency range with specialized in-depth analysis techniques to better evaluate the signal.
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AutoSignal has won the September Reader's Choice from Desktop Engineering. |
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Recognizing AutoSignal's "easy-to-use procedures," the December issue of Test and Measurement World acknowledges the signal analysis software as one of the "Best in Test" products for 1999. -- Annual award from Test and Measurement World, Chicago, 31st December 1999 |
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