Jupyter notebooks are an open-source web-based interactive coding interface that will introduce you to Python and integrate some basic coding concepts with Fourier applications, or whatever you want. You can run Jupyter notebooks on your own local laptop or computer.
Day to day signals come to us in waves: sound waves, pixels, physical vibrations. Frequency waves in data can represent change in any system in flux, such as temperature over time, or COVID test results for a population. Learn about signals in time or space and the waves that compose them.
Engineering applications require frequency filtering of wave-based signals. The Fourier transform wraps time or space-based wave signals around a circle. How "tightly" or "loosely" our wave is wrapped around the circle identifies frequency signatures that allow an engineer to analyze and manipulate images, sounds, and physical vibrations.
Behind the scenes, Fourier identifies the frequency components of an image to allow image compression or enhancement. It is useful to think about the system in flux as pixel values in space. Learn about image histograms and computer vision.
Have you ever wondered how a cell decides its fate? In each of our cells we have instructions to make any cell, so how does a neuron decide to be a neuron, or our larynx decide to be our larynx? The secret is in gene expression.
Spectra in the wild are less predictable and unevenly spaced. Waves aren't always immediately visible. Learn algorithms to help you enter frequency space in the wild.
One of my favorite images from the work of Edward Tufte is called Information Design in Space by Russian cosmonaut Georgi Grecho.