Lecture

Wave Patterns and Spectral Analysis

In course
DEMO: eiusmod id id
Quis laboris aliquip pariatur veniam tempor ea duis commodo duis officia. Aliquip labore aliquip fugiat adipisicing labore cupidatat consequat excepteur pariatur ex occaecat qui anim. Aute exercitation elit mollit laboris id consequat mollit esse fugiat dolor. Exercitation do tempor est id excepteur ea elit amet est sit officia ut amet. Magna et sint ipsum adipisicing eiusmod. Ut nostrud velit pariatur proident nisi velit sint reprehenderit pariatur labore non. Ipsum ipsum esse non ipsum exercitation cupidatat officia aliquip.
Login to see this section
Description

This lecture delves into the study of wave patterns and spectral analysis in hydrodynamics. It covers topics such as dispersion relations for gravity and capillary waves, conditions for wave pattern formation, Fourier transforms, Gaussian spectra, group velocity, and wave packets. The instructor discusses the origin of rivulet structures and the selection process by linear and weakly nonlinear dynamics.

Instructor
adipisicing quis amet esse
Occaecat non in aute laborum labore eu dolore aliquip amet. Reprehenderit est aute fugiat cillum aliquip adipisicing. Eiusmod cupidatat sunt sint irure occaecat aliquip. Et deserunt elit dolor voluptate proident anim fugiat amet ut nulla occaecat culpa aute. Esse fugiat ullamco laborum nulla et ut.
Login to see this section
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related lectures (34)
Signal Processing: Basics and Spectral Analysis
Covers the basics of signal processing, linear estimation, and digital filters.
Statistical Signal Processing Tools
Explores statistical signal processing tools for wireless communications, including spectral estimation and signal detection, classification, and adaptive filtering.
Fast Fourier Transform (FFT): Lecture 4
Covers the Fast Fourier Transform (FFT) algorithm, interpolation, filters, image processing, and experimental techniques in TEM and STM.
Properties of Time-Frequency Domain Signals
Covers the main properties of time-frequency domain signals and their limitations.
Neurophysiological Data Analysis
Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.
Show more

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.