Wavelets provide new capabilities for analyzing real-time signals. This introductory article provides an overview and presents the basic mechanisms involved in wavelets. In many signal processing ...

Fourier analysis provides a powerful framework for decomposing functions into sums or integrals of sinusoidal components, thereby enabling the study of frequency content in signals. In tandem, ...

Applications range from medical imaging to autonomous vehicle technology. Learn data manipulation techniques to improve signal or image fidelity. Understand the theory of probability and stochastic ...

Welcome to the ME 579 blog! A big thank you to Professors Jeff Rhoads and Chuck Krousgrill for getting this up and running, as well as training me on how to do stuff! The blog for the Spring 2018 ...

Signal processing is a multidisciplinary field concerned with the analysis, transformation, and interpretation of signals—functions that convey information about physical phenomena. At its core, ...

Joseph Fourier, born just 250 years ago, introduced a wonderful idea that revolutionised science and mathematics: any function or signal can be broken down into simple periodic sine-waves. Radio waves ...

Analog-to-digital converters (ADCs) are essential building blocks in modern electronic systems. They form the critical link between front-end analog transducers and back-end digital computers that can ...

As we listen to a piece of music, our ears perform a calculation. The high-pitched flutter of the flute, the middle tones of the violin, and the low hum of the double bass fill the air with pressure ...

Here you are going to write a function that uses the in-built functions pwelch and cpsd, and you are going to use the results to examine H1 and H2 estimates of H, and the coherence function. You will ...