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FFT / WAVELET APPLICATION GALLERY

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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.
 
FFT :

Perform FFT spectral analysis for accurate component frequency and power.

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FFT with Tapering Window :

Solve the leakage problem found with standard FFT methods by using one of the 30 data tapering windows included.

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Fourier Spectra of Segmented Data :

FFT spectra of segmented data makes it possible to check the assumption of stationarity by inspecting a graph of the individual spectra or by displaying all the spectra in a 3D plot. It also makes it possible to generate full error bars for the averaging across segments.

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Multitaper Spectrum :

The Fourier Multitaper spectrum is a cutting edge technique that reduces the variance of the spectral estimate using statistical methods.

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FFT of Unevenly Sampled Data :

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.

Continuous Wavelet Transform (3D) :

Easily find the time and frequency localization components simultaneously of a non - stationary periodic signal by viewing a 3D surface. Rotate the surface for better perspectives.

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CWT Contour :

Easily find the time and frequency localization components simultaneously of a non - stationary periodic signal by viewing a contour. Gradients show the critical limit levels to visualize significance.

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CWT - Frequency Range Analysis :

CWT power is integrated over frequency.

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CWT - Time Range Analysis :

CWT power is integrated over time.

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Mother Wavelet :

You can choose and adjust the mother wavelets (Morlet, Paul, Gaussian Derivative).

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