In automata theory (a branch of theoretical computer science), DFA minimization is the task of transforming a given deterministic finite automaton (DFA) into an equivalent DFA that has a minimum number of states. Here, two DFAs are called equivalent if they recognize the same regular language. Several different algorithms accomplishing this task are known and described in standard textbooks on automata theory. (Wikipedia).
Transforming an NFA into a DFA
Any non-deterministic finite state automaton (NFA) can be transformed into an equivalent deterministic finite state automaton (DFA). In this video we'll see how to make the transformation by systematically exploring an NFA.
From playlist Discrete Structures
In this video, I give you a glimpse of the field calculus of variations, which is a nice way of transforming a minimization problem into a differential equation and vice-versa. And the nice thing is that I'm not using much more than single-variable calculus, enjoy!
From playlist Partial Differential Equations
Solving Differential Equations by Separation of Variables
This video introduces the technique of separation of variables to solve differential equations.
From playlist First Order Differential Equations: Separation of Variables
Define DFA for a language in (0, 1)*, string that start and end with the same bit
We define the DFA for the language with alphabet of {0, 1} and starts and ends with the same bit
From playlist Problem Sessions in Theoretical Computer Science
Difficult to form a recipe here, but through judicious use of substitution you can infinitely simplify a DE. Have a look.
From playlist Differential Equations
Regular expressions and Non-Deterministic Finite State Automata (NFA)
A recap of converting regular expressions to non-deterministic finite state automata (NFA) with epsilon transitions, and then converting the NFA to a DFA. I used a simplified version of Thompson's Construction.
From playlist Discrete Structures
Learning Automata with Hankel Matrices - Borja Balle, Amazon Research Cambridge
The Hankel matrix is a fundamental tool in the theory of weighted automata. In this talk we will describe a general framework for learning automata with Hankel matrices. Our framework provides a unified view of many classical and recent algorithms for learning automata under different lear
From playlist Logic and learning workshop
Irrigation Efficiencies - Part 1
From playlist TEMP 1
Separable Differential Equation dy/dx = (xy + 3x - y - 3)/(xy - 2x + 4y - 8)
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Separable Differential Equation dy/dx = (xy + 3x - y - 3)/(xy - 2x + 4y - 8)
From playlist Differential Equations
Wolfram Physics Project: Working Session Tuesday, Sept. 28, 2021 [Multiway Systems Based on Numbers]
This is a Wolfram Physics Project working session about metamathematics. A previous discussion can be found here: https://youtu.be/IkQewe7cCsw Originally livestreamed at: https://twitch.tv/stephen_wolfram Stay up-to-date on this project by visiting our website: http://wolfr.am/physics Ch
From playlist Wolfram Physics Project Livestream Archive
Discrete Structures: NFA and DFA; Thompson's Constructions
Learn how to convert any NFA into an equivalent DFA. How to handle epsilon transitions. Also, using Thompson's Constructions to convert a regular expression into an NFA.
From playlist Discrete Structures, Spring 2022
Heather Kulik - Exploring multi-million compound spaces w/ chemical accuracy using machine learning
Recorded 27 March 2023. Heather Kulik of the Massachusetts Institute of Technology presents "Exploring multi-million compound spaces with chemical accuracy using machine learning" at IPAM's Increasing the Length, Time, and Accuracy of Materials Modeling Using Exascale Computing workshop. A
From playlist 2023 Increasing the Length, Time, and Accuracy of Materials Modeling Using Exascale Computing
Theory of Computation Recitation 1
Theory of Computation Recitation 1 aduni
From playlist [Shai Simonson]Theory of Computation
Differential Equations | Separation of Variables Example 3
We present a solution to a differential equation using the separation of variables technique.
From playlist Differential Equations -- Separation of Variables
What Makes Python Python? (aka Everything About Python’s Grammar)
We will try to answer a straightforward question: What makes Python so easy to learn and read? Other languages also have a robust community and a compelling ecosystem and standard library, but Python somehow stands out on how easy it is to understand existing code and how quickly and pleas
From playlist Python
Theory of Computation: Universal machines
This video is for my Spring 2020 section of MA 342, for the class meeting on Wednesday April 15. Visit the class website for homework as usual! Fast forward music is from "Now Get Busy" by the Beastie Boys, licensed Creative Commons Noncommercial Sampling Plus.
From playlist Math 342 (Theory of Computation) Spring 2020
Converting NFA to DFA: Theory of Computation (Feb 16 2021)
The subset construction to convert an NFA to an equivalent DFA. This is a recording of a live class for Math 3342, Theory of Computation, an undergraduate course for math & computer science majors at Fairfield University, Spring 2021. Class website: http://cstaecker.fairfield.edu/~cstaec
From playlist Math 3342 (Theory of Computation) Spring 2021
Perform Implicit Differentiation Using Partial Derivatives
This video explains how to find dy/dx of an implicit equation of two variables using partial derivatives.
From playlist The Chain Rule and Directional Derivatives, and the Gradient of Functions of Two Variables
Computation Ep4, Bigger DFAs (Jan 25, 2022)
This is a recording of a live class for Math 3342, Theory of Computation, an undergraduate course for math and computer science majors at Fairfield University, Spring 2022. The course is about finite automata, Turing machines, and related topics. Homework and handouts at the class websi
From playlist Math 3342 (Theory of Computation) Spring 2022