Fourier Analysis and Filtering
Transforms and filters are tools for processing and analyzing discrete data, and are commonly
used in signal processing applications and computational mathematics. When data is represented
as a function of time or space, the Fourier transform decomposes the data into frequency
components. The fft function uses a fast Fourier transform
algorithm that reduces its computational cost compared to other direct implementations. For a
more detailed introduction to Fourier analysis, see Fourier Transforms. The conv and filter functions are also useful tools for modifying the amplitude or phase of
input data using a transfer function.
Functions
Topics
The Fourier transform is a powerful tool for analyzing data across many applications, including Fourier analysis for signal processing.
Use the Fourier transform for frequency and power spectrum analysis of time-domain signals.
Transform 2-D optical data into frequency space.
Smooth noisy, 2-D data using convolution.
Filtering is a data processing technique used for smoothing data or modifying specific data characteristics, such as signal amplitude.
