Stochastic Signal Processing vs Discrete Probability

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.

Everything you need to learn and compute discrete distributions — formulas, derivations, and visual tools, all in one app. In Discrete Probability app, everything is in one place: • User-friendly calculator • Formulas with rigorous yet easy-to-follow derivations — exportable as images or LaTeX • Descriptions of optimized computation methods when they differ from the standard formulas • Histograms and other essential visual tools Covered in the first version: • General concepts with definitions and derivations / proofs • Binomial distribution • Geometric distribution • Negative Binomial distribution • Hypergeometric distribution • Poisson distribution We welcome your feedback — write to graphmath@aol.com