Frequency-domain analysis | Fourier analysis | Signal processing
The power spectrum of a time series describes the distribution of power into frequency components composing that signal. According to Fourier analysis, any physical signal can be decomposed into a number of discrete frequencies, or a spectrum of frequencies over a continuous range. The statistical average of a certain signal or sort of signal (including noise) as analyzed in terms of its frequency content, is called its spectrum. When the energy of the signal is concentrated around a finite time interval, especially if its total energy is finite, one may compute the energy spectral density. More commonly used is the power spectral density (or simply power spectrum), which applies to signals existing over all time, or over a time period large enough (especially in relation to the duration of a measurement) that it could as well have been over an infinite time interval. The power spectral density (PSD) then refers to the spectral energy distribution that would be found per unit time, since the total energy of such a signal over all time would generally be infinite. Summation or integration of the spectral components yields the total power (for a physical process) or variance (in a statistical process), identical to what would be obtained by integrating over the time domain, as dictated by Parseval's theorem. The spectrum of a physical process often contains essential information about the nature of . For instance, the pitch and timbre of a musical instrument are immediately determined from a spectral analysis. The color of a light source is determined by the spectrum of the electromagnetic wave's electric field as it fluctuates at an extremely high frequency. Obtaining a spectrum from time series such as these involves the Fourier transform, and generalizations based on Fourier analysis. In many cases the time domain is not specifically employed in practice, such as when a dispersive prism is used to obtain a spectrum of light in a spectrograph, or when a sound is perceived through its effect on the auditory receptors of the inner ear, each of which is sensitive to a particular frequency. However this article concentrates on situations in which the time series is known (at least in a statistical sense) or directly measured (such as by a microphone sampled by a computer). The power spectrum is important in statistical signal processing and in the statistical study of stochastic processes, as well as in many other branches of physics and engineering. Typically the process is a function of time, but one can similarly discuss data in the spatial domain being decomposed in terms of spatial frequency. (Wikipedia).
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Representation of wide sense stationary random processes in the frequency domain - the power spectral density or power spectrum is the DTFT of the a
From playlist Random Signal Characterization
Physical Science 3.4b - Density
Density. The definition of density, the equation for density, and some numerical examples.
From playlist Physical Science Chapter 3 (Complete chapter)
(PP 6.4) Density for a multivariate Gaussian - definition and intuition
The density of a (multivariate) non-degenerate Gaussian. Suggestions for how to remember the formula. Mathematical intuition for how to think about the formula.
From playlist Probability Theory
What is Relative Density? | Physics | Don't Memorise
Now that you know what Density means, it would be quite easy for you to understand what Relative Density means. Watch this video to know more. ✅To learn more about Relative Density enroll in our full course now: https://infinitylearn.com/microcourses?utm_source=youtube&utm_medium=Soical&
From playlist Physics
What is Density? | Gravitation | Physics | Don't Memorise
Understanding the concept of Density is very important in order to understand Physics. Watch this video to fully grasp the idea of density. To get access to the entire course based on Gravitation, enroll here: https://infinitylearn.com/microcourses?utm_source=youtube&utm_medium=Soical&u
From playlist Physics
Physics - E&M: Ch 40.1 Current & Resistance Understood (16 of 17) What is Current Density?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain the current density, for example, of a conductor of a given current (I) and current density (J) is defined as the amount of current per unit area. Next video in this series can be seen at: ht
From playlist THE "WHAT IS" PLAYLIST
Astronomy - Ch. 7: The Solar Sys - Comparative Planetology (7 of 33) Planet Density
Visit http://ilectureonline.com for more math and science lectures! In this video I will discuss the various densities of the planets in our Solar System.. Next video in this series can be seen at: http://youtu.be/n7IOTMcEDws
From playlist ASTRONOMY 7B THE SOLAR SYSTEM - COMPARATIVE PLANETOLOGY
Spectral Sequences 02: Spectral Sequence of a Filtered Complex
I like Ivan Mirovic's Course notes. http://people.math.umass.edu/~mirkovic/A.COURSE.notes/3.HomologicalAlgebra/HA/2.Spring06/C.pdf Also, Ravi Vakil's Foundations of Algebraic Geometry and the Stacks Project do this well as well.
From playlist Spectral Sequences
Vicky Fasen-Hartmann: Empirical spectral processes for stationary state space models
In this talk, we consider function-indexed normalized weighted integrated periodograms for equidistantly sampled multivariate continuous-time state space models which are multivariate continuous-time ARMA processes. Thereby, the sampling distance is fixed and the driving Lévy process has a
From playlist Probability and Statistics
Lec 20b - Phys 237: Gravitational Waves with Kip Thorne
Watch the rest of the lectures on http://www.cosmolearning.com/courses/overview-of-gravitational-wave-science-400/ Redistributed with permission. This video is taken from a 2002 Caltech on-line course on "Gravitational Waves", organized and designed by Kip S. Thorne, Mihai Bondarescu and
From playlist Caltech: Gravitational Waves with Kip Thorne - CosmoLearning.com Physics
Michael Bertolacci - AdaptSPEC-X: Spectral analysis of multiple non stationary time series
Dr Michael Bertolacci (University of Wollongong) presents “AdaptSPEC-X: Spectral analysis of multiple non stationary time series”, 08/10/2020. Seminar organised by ANU.
From playlist Statistics Across Campuses
Spectral Function in Bilayer Graphene: Quasiparticles and Plasmarons - Rajdeep Sensarma
DISCUSSION MEETING : ADVANCES IN GRAPHENE, MAJORANA FERMIONS, QUANTUM COMPUTATION DATES Wednesday 19 Dec, 2012 - Friday 21 Dec, 2012 VENUE Auditorium, New Physical Sciences Building, IISc Quantum computation is one of the most fundamental and important research topics today, from both th
From playlist Advances in Graphene, Majorana fermions, Quantum computation
Suhasini Subba Rao: Reconciling the Gaussian and Whittle Likelihood with an application to ...
In time series analysis there is an apparent dichotomy between time and frequency domain methods. The aim of this paper is to draw connections between frequency and time domain methods. Our focus will be on reconciling the Gaussia likelihood and the Whittle likelihood. We derive an exact,
From playlist Virtual Conference
A Spectral Index Study of the Jets in MOJAVE by Talvikki Hovatta
Extragalactic Relativistic Jets: Cause and Effect PROGRAM LINK: www.icts.res.in/program/ERG2015 DATES: Monday 12 Oct, 2015 - Tuesday 20 Oct, 2015 VENUE: Ramanujan Lecture Hall, ICTS Bangalore DESCRIPTION : Active Galactic Nuclei (AGN) are the luminous centers of galaxies that are belie
From playlist Extragalactic Relativistic Jets: Cause and Effect
Absolute continuity of limiting spectral distributions of Toeplitz... by Manjunath Krishnapur
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
Astronomy - The Sun (14 of 16) The Corona
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain the corona.
From playlist ASTRONOMY 16 THE SUN
Suhasini Subba Rao: Fourier based methods for spatial data observed on irregularly spaced locations
Abstract : In this talk we introduce a class of statistics for spatial data that is observed on an irregular set of locations. Our aim is to obtain a unified framework for inference and the statistics we consider include both parametric and nonparametric estimators of the spatial covarianc
From playlist Probability and Statistics
Lec 17 | MIT 6.450 Principles of Digital Communications I, Fall 2006
Lecture 17: Detection for random vectors and processes View the complete course at: http://ocw.mit.edu/6-450F06 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.450 Principles of Digital Communications, I Fall 2006
Physics - E&M: Ch 40.1 Current & Resistance Understood (17 of 17) What is Current Density? Ex.
Visit http://ilectureonline.com for more math and science lectures! In this video I will find the current density, J=?, given current, I=4amps, and diameter, D=2mm. First video in this series can be seen at: https://youtu.be/bDe4lzgQY2E
From playlist THE "WHAT IS" PLAYLIST