Filter Menu

The Filter menu offers signal processing procedures that modify the data table by smoothing, removing noise, and isolating components. These include advanced processing procedures in the Fourier and Eigendecomposition domains.

The Automated Smoothing option simplifies the use of six different procedures for smoothing the data table.

The Savitzky-Golay Smoothing procedure offers effective time-domain smoothing for data sets with uniform X-spacing. The algorithm offers adjustable order (quartic is typical), automatic sequential passes (three is about optimum), and optional first through eighth smoothed derivatives.

The Fourier Denoising option is a specialized Fourier filtration procedure that sets either a frequency threshold for low pass frequency-domain filtration, or a signal threshold for zeroing all spectral elements below a given power. The time domain data are reconstructed using the inverse FFT.

The Eigendecomposition Denoising option accomplishes a similar function except that the filtration occurs by zeroing those eigenmodes that contain noise. By using a high order decomposition, it is often possible to remove nearly all of the noise within a signal.

The Fourier Filtering option is an extensive Fourier domain filtering and component isolation procedure. This procedure supports data tapering windows so that low power components can be isolated and reconstructed.

The Eigendecomposition Filtering option offers full eigenmode filtering and reconstruction. Eigendecomposition partitions by signal strength rather than by frequency. In addition to the data, the reconstruction can optionally consist of the eigenvectors, the principal components, the data components, FFTs of the data components, or an FFT spectrum of the data.