Ergodic theory | Dynamical systems
In mathematics, a Markov odometer is a certain type of topological dynamical system. It plays a fundamental role in ergodic theory and especially in orbit theory of dynamical systems, since a theorem of H. Dye asserts that every ergodic nonsingular transformation is orbit-equivalent to a Markov odometer. The basic example of such system is the "nonsingular odometer", which is an additive topological group defined on the product space of discrete spaces, induced by addition defined as , where . This group can be endowed with the structure of a dynamical system; the result is a conservative dynamical system. The general form, which is called "Markov odometer", can be constructed through Bratteli–Vershik diagram to define Bratteli–Vershik compactum space together with a corresponding transformation. (Wikipedia).
Prob & Stats - Markov Chains (8 of 38) What is a Stochastic Matrix?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is a stochastic matrix. Next video in the Markov Chains series: http://youtu.be/YMUwWV1IGdk
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
Markov Chains Clearly Explained! Part - 1
Let's understand Markov chains and its properties with an easy example. I've also discussed the equilibrium state in great detail. #markovchain #datascience #statistics For more videos please subscribe - http://bit.ly/normalizedNERD Markov Chain series - https://www.youtube.com/playl
From playlist Markov Chains Clearly Explained!
24. Markov Matrices; Fourier Series
MIT 18.06 Linear Algebra, Spring 2005 Instructor: Gilbert Strang View the complete course: http://ocw.mit.edu/18-06S05 YouTube Playlist: https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8 24. Markov Matrices; Fourier Series License: Creative Commons BY-NC-SA More information at htt
From playlist MIT 18.06 Linear Algebra, Spring 2005
Coding Challenge #42.1: Markov Chains - Part 1
In Part 1 of this Coding Challenge, I discuss the concepts of "N-grams" and "Markov Chains" as they relate to text. I use Markova chains to generate text automatically based on a source text. 💻Challenge Webpage: https://thecodingtrain.com/CodingChallenges/042.1-markov-chains.html 💻Program
From playlist Programming with Text - All Videos
Prob & Stats - Markov Chains (9 of 38) What is a Regular Matrix?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is a regular matrix. Next video in the Markov Chains series: http://youtu.be/loBUEME5chQ
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
Nexus Trimester - Omri Weinstein (Courant Institute (NYU)) 6/6
An Interactive Information Odometer and Applications Omri Weinstein (Courant Institute (NYU)) February 09, 2016 Abstract: Communication complexity had a profound impact on nearly every field of theoretical computer science, and is one of the rare methods for proving unconditional lower b
From playlist Nexus Trimester - 2016 - Distributed Computation and Communication Theme
Special Topics - The Kalman Filter (18 of 55) What is a Covariance Matrix?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is the state covariance matrix, process noise covariance matrix, and measurement covariance matrix. Next video in this series can be seen at: https://youtu.be/ieL0jxzLhCE
From playlist SPECIAL TOPICS 1 - THE KALMAN FILTER
Absorbing-State Phase Transitions by Leonardo Rolla
PROGRAM :UNIVERSALITY IN RANDOM STRUCTURES: INTERFACES, MATRICES, SANDPILES ORGANIZERS :Arvind Ayyer, Riddhipratim Basu and Manjunath Krishnapur DATE & TIME :14 January 2019 to 08 February 2019 VENUE :Madhava Lecture Hall, ICTS, Bangalore The primary focus of this program will be on the
From playlist Universality in random structures: Interfaces, Matrices, Sandpiles - 2019
Markov Chains: n-step Transition Matrix | Part - 3
Let's understand Markov chains and its properties. In this video, I've discussed the higher-order transition matrix and how they are related to the equilibrium state. #markovchain #datascience #statistics For more videos please subscribe - http://bit.ly/normalizedNERD Markov Chain ser
From playlist Markov Chains Clearly Explained!
Prob & Stats - Markov Chains (4 of 38) Another Way to Calculate the Markov Chains
Visit http://ilectureonline.com for more math and science lectures! In this video I will show an alternative method to calculate the 2nd, 3rd, 4th,...states of Markov chain. Next video in the Markov Chains series: http://youtu.be/9wBPa2eu_lc
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
REGRESSION: Non-Linear relationships & Logarithms
All my stats videos are found here: http://www.zstatistics.com/ See the whole regression series here: https://www.youtube.com/playlist?list=PLTNMv857s9WUI1Nz4SssXDKAELESXz-bi To download the jaybob.csv dataset, head over to the website above, I'll upload the data (and associated model wo
From playlist Regression series (10 videos)
The History of Maps | Petersen Workshop
In today's video, we take a look at the History of Maps. Maps are a important piece of Automotive History, without them, we wouldn't have been able to get to our destination. Maps present information about the world or place in a simple, visual way. We join our host, Ron Baugh in giving us
From playlist Petersen Workshop
Olga Lukina: Rotated odometers
We consider infinite interval exchange transformations (IETs) obtained as a composition of a finite IET and the von Neumann-Kakutani map, called rotated odometers, and study their dynamical and ergodic properties by means of an associated Bratteli-Vershik system. We show that every rotated
From playlist Virtual Conference
WHAT MAKES IT WORK? #19 "How a Speedometer Works" tubalcain
WATCH ALL THE 20 VIDEOS IN THIS SERIES! I have 700 videos under the name TUBALCAIN: Watch them all & SUBSCRIBE!
From playlist WHAT MAKES IT WORK?
Prob & Stats - Markov Chains (10 of 38) Regular Markov Chain
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is a regular Markov chain. Next video in the Markov Chains series: http://youtu.be/DeG8MlORxRA
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
Data Science Fundamentals: Linear Regression
In this video, I walk you through a simple linear regression and a multiple linear regression model using the ordinary least squares method. I build on the previous data science fundamental videos. #DataScience #DataScienceFundamentals #LinearRegression #Python Github: https://github.com
From playlist Data Science Fundamentals
Abelian networks and sandpile models (Lecture 3) by Lionel Levine
PROGRAM :UNIVERSALITY IN RANDOM STRUCTURES: INTERFACES, MATRICES, SANDPILES ORGANIZERS :Arvind Ayyer, Riddhipratim Basu and Manjunath Krishnapur DATE & TIME :14 January 2019 to 08 February 2019 VENUE :Madhava Lecture Hall, ICTS, Bangalore The primary focus of this prog
From playlist Universality in random structures: Interfaces, Matrices, Sandpiles - 2019
Calculus made easy, the Mathologer way :) 00:00 Intro 00:49 Calculus made easy. Silvanus P. Thompson comes alive 03:12 Part 1: Car calculus 12:05 Part 2: Differential calculus, elementary functions 19:08 Part 3: Integral calculus 27:21 Part 4: Leibniz magic notation 30:02 Animations: prod
From playlist Recent videos
Data Science Fundamentals: Data Cleaning in Python
This is the third video in my Data Science Fundamentals series. In it I walk through the most important data cleaning techniques using pandas. Data cleaning is extremely important process in data science. There is an old adage in data science "garbage in garbage out", if we don't provide c
From playlist Data Science Fundamentals
Prob & Stats - Markov Chains (20 of 38) Absorbing Markov Chains - Definition 2
Visit http://ilectureonline.com for more math and science lectures! In this video I will define the absorbing Markov in a nxn matrix and 3x3 matrix. Next video in the Markov Chains series: http://youtu.be/cZKAVOEWcrg
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes