Loughborough Wave Lab vs Stochastic Signal Processing

Loughborough Wave Lab is an educational learning app designed to aid students in their understanding of electromagnetic wave concepts in an engaging and entertaining way! Features include: • Virtual pond • Persistent Sinusoidal Pulses • Virtual Ripple Tank • Waveguide Simulator • Young's Double Slit Experiment • Custom Simulation Mode Loughborough Wave Lab is intended to accompany teaching on Electromagnetic phenomena and to provide students with an interactive way of seeing these principles in action! Educators can now author their own custom simulation files, upload them to a web server and then have Loughborough Wave Lab execute the simulations using a WiFi or cellular data connection to download the configurations and display them to the user. This uses the new, open-source configuration standard CEML which has been introduced by the developer (available at www.github.com/danielrbrowne/CEML)

Speech, music, seismic vibrations, oil prices, and climate measurements are all examples of stochastic (random) signals. In this textbook—intended for individuals with prior training in introductory signal processing and introductory probability theory—we develop techniques to process such signals to extract useful information. We present case studies ranging from music to photographic images to oil prices to climate data to the motion of individual biomolecules. This textbook, as an interactive textbook ("iBook"), makes use of your device's ability to display dynamic information through films and animations and to hear the results of the techniques applied to music. At the end of every chapter there are homework problems ranging from easy to "olympic". We make use of your device's interactive capabilities to offer 59 laboratory experiments in signal processing. The experiments use the camera, the microphone, the speakers, and the graphical user interface. These experiments are not simulations; they are examples of real digital processing of signals in your device. In this time of at-home and online learning, this is the way to learn signal processing through study and experimentation.