Exponential family distributions | Complex distributions | Conjugate prior distributions | Continuous distributions | Covariance and correlation | Multivariate continuous distributions
The complex inverse Wishart distribution is a matrix probability distribution defined on complex-valued positive-definite matrices and is the complex analog of the real inverse Wishart distribution. The complex Wishart distribution was extensively investigated by Goodman while the derivation of the inverse is shown by Shaman and others. It has greatest application in least squares optimization theory applied to complex valued data samples in digital radio communications systems, often related to Fourier Domain complex filtering. Letting be the sample covariance of independent complex p-vectors whose Hermitian covariance has complex Wishart distribution with mean value degrees of freedom, then the pdf of follows the complex inverse Wishart distribution. (Wikipedia).
Ex 1: Find the Inverse of a Function
This video provides two examples of how to determine the inverse function of a one-to-one function. A graph is used to verify the inverse function was found correctly. Library: http://mathispower4u.com Search: http://mathispower4u.wordpress.com
From playlist Determining Inverse Functions
Complex Analysis: Inverse Laplace Transform 1/sqrt(s)
Today, we evaluate the inverse Laplace transform of 1/sqrt(s) using a combination of the Bromwich and keyhole contour. ILT Lemma: https://www.youtube.com/watch?v=yfL-9JljvEQ
From playlist Complex Analysis
A Random Matrix Bayesian framework for out-of-sample quadratic optimization - Marc Potters
Marc Potters CFM November 6, 2013 For more videos, please visit http://video.ias.edu
From playlist Mathematics
The Role of the Transpose in Free Probability - J.Mingo - Workshop 2 - CEB T3 2017
James Mingo / 26.10.17 The Role of the Transpose in Free Probability: the partial transpose of R-cyclic operators Like tensor independence, free independence gives us rules for doing calculations. With random matrix models, we usually need tensor independence of the entries and some kin
From playlist 2017 - T3 - Analysis in Quantum Information Theory - CEB Trimester
Exploring the random landscapes of inference (Lecture 2) by Gérard Ben Arous
DISCUSSION MEETING : STATISTICAL PHYSICS OF MACHINE LEARNING ORGANIZERS : Chandan Dasgupta, Abhishek Dhar and Satya Majumdar DATE : 06 January 2020 to 10 January 2020 VENUE : Madhava Lecture Hall, ICTS Bangalore Machine learning techniques, especially “deep learning” using multilayer n
From playlist Statistical Physics of Machine Learning 2020
Composition of inverses using a triangle with variables
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
For the latest information, please visit: http://www.wolfram.com Speaker: Hsien-Ching Kao Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mobile devices, and more.
From playlist Wolfram Technology Conference 2015
Evaluating the composition of cosine and sine inverse
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Ex 2: Find the Inverse of a Function
This video provides two examples of how to determine the inverse function of a one-to-one function. A graph is used to verify the inverse function was found correctly. Library: http://mathispower4u.com Search: http://mathispower4u.wordpress.com
From playlist Determining Inverse Functions
James Mingo: The infinitesimal Weingarten calculus
Talk at the conference "Noncommutative geometry meets topological recursion", August 2021, University of Münster. Abstract: The Weingarten calculus calculates matrix integrals over the unitary and orthogonal groups, in particular their large N behaviour. In this talk we shall look at the W
From playlist Noncommutative geometry meets topological recursion 2021
Ex: Evaluate Basic Inverse Trig Expressions Involving Arcsine Using the Unit Circle
This video explains how to evaluate inverse trig expressions involving arcsine using the unit circle. Answers are checked on a graphing calculator. Site: http://mathispower4u.com
From playlist Inverse Trigonometric Functions
How to graph the inverse sine given the graph of sine
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Asymptotic properties of random quantum states and channels - Z.Puchała - Workshop 2 - CEB T3 2017
Zbigniew Puchała / 21.10.17 Asymptotic properties of random quantum states and channels Properties of random mixed states of dimension N distributed uniformly with respect to the Hilbert-Schmidt measure are investigated. We show that for large N, due to the concentration of measure pheno
From playlist 2017 - T3 - Analysis in Quantum Information Theory - CEB Trimester
Lecture 15 - EM Algorithm & Factor Analysis | Stanford CS229: Machine Learning Andrew Ng -Autumn2018
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3jsY9n7 Andrew Ng Adjunct Professor of Computer Science https://www.andrewng.org/ To follow along with the course schedule and syllabus, visit: http://cs229.sta
From playlist Stanford CS229: Machine Learning Full Course taught by Andrew Ng | Autumn 2018
Evaluate the composition of sine and sine inverse
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Top Eigenvalue of a Random Matrix: A tale of tails - Satya Majumdar
Speaker : Satya Majumdar (Directeur de Recherche in CNRS) Date and Time : 27 Jan 2012, 04:00 PM Venue : New Physical Sciences Building Auditorium, IISc, Bangalore Random matrices were first introduced by Wishart (1928) in the statistics literature to describe the covariance matrix of la
From playlist Top Eigenvalue of a Random Matrix: A tale of tails - Satya Majumdar
Learn how to evaluate the composition of a function and inverse function
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Eigenvalue Rigidity in Random Matrices and Applications in Last... by Riddhipratim Basu
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
The Derivatives of Inverse Trigonometric Functions
This video explains how to determine the derivatives of inverse trigonometric functions. http://mathispower4u.wordpress.com/
From playlist Differentiation