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Fast Fourier Transform (FFT)

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This nodes performs a Fast Fourier Transform in a desired numeric timeseries data column. It requires the KNIME Python extensions with Python 3 set up. The dataset cannot contain missing values. Additionally, the component produces an interactive view displaying the normalized power spectrum of the signal. The component requires the following extensions: - KNIME Python Integration (https://kni.me/e/9Z2SYIHDiATP4xQK) - KNIME JavaScript Views (https://kni.me/e/0qveOxOA3751S6Vx) Topics: IoT, Internet of Things, Signal Processing

Component details

Input ports
  1. Type: Table
    Input Data
    The Input data. It should contain a numeric time series column.
Output ports
  1. Type: Table
    Transformed table
    Output a table containing the original columns and two adittional columns with the resolved frequencies and their normalized power. Normalization is performed by dividing the raw amplitudes by the length of the signal.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.2.0
  • KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

  • KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

  • KNIME Plotly Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

  • KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

  • KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0