INTRODUCTIONFourier transform was first devised by Jean-Baptiste Joseph Fourier 8th century French mathematician.A Fourier transform is a way of decomposing a signal into pure sine waves, each with its own amplitude and frequency that add to make it up.Some of the applications of Fourier transform are as follows:Signal Processing: Filtering, CompressionCommunication Systems : Modulation and Demodulation, Spectrum Analysis:Audio Processing : Audio Compression, EqualizationImage Processing : Image Analysis, Image CompressionMedical Imaging : MRI and CT ImagingPhysics : Quantum Mechanics, SpectroscopyControl Systems : System Analysis, Filter DesignVibration Analysis : Structural Health Monitoring, Modal AnalysisElectrical Engineering : Power System Analysis, Filter DesignSeismology : Earthquake AnalysisFourier Transform can be done on signals as infinite continuous waves and when you take their Fourier transform, you get an infinite continuous frequency spectrum.But real-world signals are not continuous. They are finite and made up of individual samples or data points obtained from the sensors. Considering an example of seismometer, even if a seismometer signal looks smooth and continuous, it doesn’t record ground motion with infinite precision. There is some fundamental graininess to the data so what we obtain is discreet finite data. So, we can’t use the idealized Fourier transform. Instead, you must perform a Discreet Fourier Transform.