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
Teach Astronomy - Apparent Brightness
http://www.teachastronomy.com/ Apparent Brightness in astronomy is the number of photons per second collected at the Earth from an astronomical source. It depends on three things: First, the collecting area of the device used to observe the source of light. In the case of a telescope, t
From playlist 14. Stars
Spectrum of Hg Lamp / amazing science experiment
Identify the spectral lines of Hg lamp Enjoy the amazing colors! Music: https://www.bensound.com/
From playlist Optics
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
Ana Romero: Effective computation of spectral systems and relation with multi-parameter persistence
Title: Effective computation of spectral systems and their relation with multi-parameter persistence Abstract: Spectral systems are a useful tool in Computational Algebraic Topology that provide topological information on spaces with generalized filtrations over a poset and generalize the
From playlist AATRN 2022
Astronomy - Ch. 17: The Nature of Stars (10 of 37) Relationship Between Intensity and Luminosity
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain the relationship between intensity and luminosity. Next video can be seen at: http://youtu.be/hhj0mhvLLiY
From playlist ASTRONOMY 17 STARS AND THE H-R DIAGRAM
Spectral Theory 7 - Spectral Theorem for Compact Operators (Functional Analysis - Part 34)
Support the channel on Steady: https://steadyhq.com/en/brightsideofmaths Or support me via PayPal: https://paypal.me/brightmaths Watch the whole series: https://thebrightsideofmathematics.com/functional_analysis/overview/ Functional analysis series: https://www.youtube.com/playlist?list=P
From playlist Functional analysis
Irrigation Efficiencies - Part 1
From playlist TEMP 1
Lec 2 | MIT 6.451 Principles of Digital Communication II
Performance of Small Signal Constellations View the complete course: http://ocw.mit.edu/6-451S05 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.451 Principles of Digital Communication II
High dimensional estimation via Sum-of-Squares Proofs – D. Steurer & P. Raghavendra – ICM2018
Mathematical Aspects of Computer Science Invited Lecture 14.6 High dimensional estimation via Sum-of-Squares Proofs David Steurer & Prasad Raghavendra Abstract: Estimation is the computational task of recovering a ‘hidden parameter’ x associated with a distribution 𝒟_x, given a ‘measurem
From playlist Mathematical Aspects of Computer Science
Strong refutation of semi-random Boolean CSPs - Venkatesan Guruswami
Computer Science/Discrete Mathematics Seminar I Topic: Strong refutation of semi-random Boolean CSPs Speaker: Venkatesan Guruswami Affiliation: Carnegie Mellon University Date: March 08, 2021 For more video please visit http://video.ias.edu
From playlist Mathematics
Lec 3 | MIT 6.451 Principles of Digital Communication II
Hard-decision and Soft-decision Decoding View the complete course: http://ocw.mit.edu/6-451S05 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.451 Principles of Digital Communication II
14. PV Efficiency: Measurement and Theoretical Limits
MIT 2.627 Fundamentals of Photovoltaics, Fall 2011 View the complete course: http://ocw.mit.edu/2-627F11 Instructor: Tonio Buonassisi This lecture examines the practical realization and theoretical limits of solar cell efficiency, with a closer look at solar simulators, making measurement
From playlist MIT 2.627 Fundamentals of Photovoltaics, Fall 2011
The Power of Nonlinearities - A. Marandi - 11/11/2020
Earnest C. Watson Lecture by Professor Marandi, "The Power of Nonlinearities: Unlocking Opportunities for Sensing and Computing with Light." As the information age evolves, we are faced with new challenges in how to capture and process information. Nonlinearity, which leads to functions
From playlist Caltech Watson Lecture Series
Álvaro Torras Casas (8/5/20): The Persistence Mayer-Vietoris spectral sequence
Title: The Persistence Mayer Vietoris spectral sequence Abstract: In this talk, I will give a brief introduction to the persistent Mayer-Vietoris spectral sequence. The original motivation for studying this object comes from the need to parallelize persistent homology computations. The st
From playlist AATRN 2020
Primordial Black Hole DM - II (Lecture 1) by Yacine Ali Haimoud
PROGRAM LESS TRAVELLED PATH OF DARK MATTER: AXIONS AND PRIMORDIAL BLACK HOLES (ONLINE) ORGANIZERS: Subinoy Das (IIA, Bangalore), Koushik Dutta (IISER, Kolkata / SINP, Kolkata), Raghavan Rangarajan (Ahmedabad University) and Vikram Rentala (IIT Bombay) DATE: 09 November 2020 to 13 Novemb
From playlist Less Travelled Path of Dark Matter: Axions and Primordial Black Holes (Online)
Mario Figueiredo: ADMM in Imaging Inverse Problems: Some History and Recent Advances
Abstract: The alternating direction method of multipliers (ADMM) is an optimization tool of choice for several imaging inverse problems, namely due its flexibility, modularity, and efficiency. In this talk, I will begin by reviewing our earlier work on using ADMM to deal with classical pro
From playlist Analysis and its Applications
3 Easy Steps to Understand and Implement Spectral Clustering in Python
This video explains three simple steps to understand the Spectral Clustering algorithm: 1) forming the adjacency matrix of the similarity graph, 2) eigenvalue decomposition of the normalized adjacency matrix or Laplacian matrix, and 3) applying the KMeans clustering algorithm to the rows o
From playlist Unsupervised Clustering Methods - Dr. Data Science Series
Teach Astronomy - Spectral Bands
http://www.teachastronomy.com/ Atoms produce sharp spectral features of emission or absorption corresponding to the specific energy states of the atom. Each element has its own set of energy states. Atoms that are grouped into molecules have a much larger set of possible energy states, i
From playlist 06. Optics and Quantum Theory