Discrete-Time Dynamical Systems
This video shows how discrete-time dynamical systems may be induced from continuous-time systems. https://www.eigensteve.com/
From playlist Data-Driven Dynamical Systems
Understanding Discrete Event Simulation, Part 1: What Is Discrete Event Simulation
Watch more MATLAB Tech Talks: https://goo.gl/ktpVB7 Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE Learn the basics of discrete-event simulation, and explore how you can use it to build a process model in this MATLAB® Tech
From playlist Understanding Discrete-Event Simulation - MATLAB Tech Talks
Understanding Discrete Event Simulation, Part 2: Why Use Discrete Event Simulation
Watch more MATLAB Tech Talks: https://goo.gl/ktpVB7 Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE Learn how discrete-event simulation can help you solve problems related to scheduling, resource allocation, and capacity pl
From playlist Understanding Discrete-Event Simulation - MATLAB Tech Talks
Connecting discrete and continuous systems
To have an effect in the real world, discrete systems have to sample sample continuous signals to operate on them and reconstruct their outputs to continuous signals. This video explains this and the problems associated with the z transform
From playlist Discrete
Understanding Discrete Event Simulation, Part 3: Leveraging Stochastic Processes
Watch more MATLAB Tech Talks: https://goo.gl/ktpVB7 Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE Learn how discrete-event simulation uses stochastic processes, in which aspects of a system are randomized, in this MATLAB®
From playlist Understanding Discrete-Event Simulation - MATLAB Tech Talks
Review of Linear Time Invariant Systems
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Review: systems, linear systems, time invariant systems, impulse response and convolution, linear constant-coefficient difference equations
From playlist Introduction and Background
Closed loop discrete controller Lecture 2019-04-08
Evaluating the response of a continuous system controlled by a discrete controller using several methods
From playlist Discrete
DISCRETE Random Variables: Finite and Infinite Distributions (9-2)
A Discrete Random Variable is any outcome of a statistical experiment that takes on discrete (i.e., separate and distinct) numerical values. Discrete outcomes: all potential outcomes numerical values are integers (i.e., whole numbers). They cannot be negative. Using an example of tests in
From playlist Discrete Probability Distributions in Statistics (WK 9 - QBA 237)
Introduction to Discrete and Continuous Functions
This video defines and provides examples of discrete and continuous functions.
From playlist Introduction to Functions: Function Basics
Feedback Control of Hybrid Dynamical Systems
Hybrid systems have become prevalent when describing complex systems that mix continuous and impulsive dynamics. Continuous dynamics usually govern the evolution of the physical variables in a system, while impulsive (or discrete) behavior is typically due to discrete events and abrupt cha
From playlist Complete lectures and talks: slides and audio
Anter El-Azab: Mesoscale crystal plasticity based on continuum dislocation dynamics
Anter El-Azab: Mesoscale crystal plasticity based on continuum dislocation dynamics: mathematical formalism and numerical solution The lecture was held within the framework of the Hausdorff Trimester Program Multiscale Problems: Workshop on Non-local Material Models and Concurrent Multisc
From playlist HIM Lectures: Trimester Program "Multiscale Problems"
Stanford Seminar - Model Predictive Control of Hybrid Dynamical Systems
Ricardo Sanfelice UC Santa Cruz November 8, 2019 Hybrid systems model the behavior of dynamical systems in which the states can evolve continuously and, at isolate time instances, exhibit instantaneous jumps. Such systems arise when control algorithms that involve digital devices are appl
From playlist Stanford AA289 - Robotics and Autonomous Systems Seminar
Deep Reinforcement Learning of Marked Temporal Point Processes by Abir De
DISCUSSION MEETING THE THEORETICAL BASIS OF MACHINE LEARNING (ML) ORGANIZERS: Chiranjib Bhattacharya, Sunita Sarawagi, Ravi Sundaram and SVN Vishwanathan DATE : 27 December 2018 to 29 December 2018 VENUE : Ramanujan Lecture Hall, ICTS, Bangalore ML (Machine Learning) has enjoyed tr
From playlist The Theoretical Basis of Machine Learning 2018 (ML)
Nonlinear Dynamics of Complex Systems:
Multi-Dimensional Time Series, Network Inference and Nonequilibrium Tipping - by Prof. Marc Timme - Lecture I
From playlist Networked Complexity
Lecture 12 | MIT 6.832 Underactuated Robotics, Spring 2009
Lecture 12: Walking (continued) Instructor: Russell Tedrake See the complete course at: http://ocw.mit.edu/6-832s09 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.832 Underactuated Robotics, Spring 2009
Meghan Heintz: Launching a new warehouse with SimPy at Rent the Runway | PyData New York City 2019
Opening a warehouse is a long and challenging process, not to mention costly. So if you're going to go through all that work to open and operate a warehouse, you'll want to make sure you can run it as efficiently as possible. Enter SimPy (rhymes with "Blimpie"). SimPy is a discrete event s
From playlist Simulations DES, AMB
Discrete Structures, Oct 20: Counting
Combinations, Permutations, Pigeonhole Principle
From playlist Discrete Structures