dept computer science p j af rik univerzity ko ice
play

Dept. Computer Science, P.J. af rik Univerzity Ko ice, Slovakia - PowerPoint PPT Presentation

Oct 09, 2023 •165 likes •1.41k views

Viliam Geffert Zuzana Bednrov Dept. Computer Science, P.J. af rik Univerzity Ko ice, Slovakia Nondeterministic pushdown automata input tape A = ( Q, ,,H,q I ,F ) . . . x 1 x 2 x 3 x n Q -- finite set of states, -- input

  1. Witness language – lower bound CASE 1 CR ∉ L C h CR w 1 u 1 w 1 $ u 2 q l q k  u’ y l x l x k $ CR u 1 w 1 w 1 CR u 2

  2. Witness language – lower bound CASE 1 CR ∉ L C h CR w 1 u 1 w 1 $ u 2 q l q k  u’ y l x l x k $ CR u 1 w 1 w 1 CR u 2

  3. Summing up: For L , we have NPDA with n + O(| Σ |) states n pushdown height | Σ | pushdown symbols On the other hand, each NPDA for L C requires at least states 2 | Σ | n-O(1) or pushdown height

  4. Witness language by two-way machine Lem.: For each Σ and n ≥ 1, language L C can be accepted by constant height 2 DPDA using n + 6| Σ |+21 states n + 1 pushdown height | Σ |+1 pushdown symbols

  5. Witness language by two-way machine Well formed input? ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP q . . . state X I pushdown

  6. Witness language by two-way machine Well formed input? (Exactly one “$” ?) ├ $ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP q . . . state X I pushdown

  7. Witness language by two-way machine Well formed input? ├ $ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP q state X I pushdown

  8. Witness language by two-way machine Well formed input? (All blocks of equal length?) ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP q 0 state X I pushdown

  9. Witness language by two-way machine Well formed input? ├ 0 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 TOP q 1 state X I pushdown

  10. Witness language by two-way machine Well formed input? ├ 0 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 TOP q 2 state X I pushdown

  11. Witness language by two-way machine Well formed input? ├ 0 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 TOP q 3 state X I pushdown

  12. Witness language by two-way machine Well formed input? ├ 0 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 TOP q 4 state X I pushdown

  13. Witness language by two-way machine Well formed input? ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 . . . 4 TOP q 0 state X I pushdown

  14. Witness language by two-way machine Well formed input? ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP q 0 state X I pushdown

  15. Witness language by two-way machine Well formed input? ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 . . . 4 TOP q state X I pushdown

  16. Witness language by two-way machine Well formed input? ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 . . . 4 TOP YES n + O(1) states X I pushdown

  17. Witness language by two-way machine Idea ? ∃ Z : R x i = Z = y j ├ ┤ 1 0 1 1 ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 1 q 0 state Z 1 1 X I pushdown

  18. Witness language by two-way machine Idea ? ∃ Z : R x i = Z = y j ├ ┤ 1 0 1 1 1 1 0 1 ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 $ 0 0 0 1 1 0 1 0 0 1 0 0 TOP 1 q 0 state Z 1 1 X I pushdown

  19. Witness language by two-way machine Initialize PD memory 4 ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 q state TOP X I pushdown

  20. Witness language by two-way machine Initialize PD memory 4 ├ 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 q state TOP 0 X I pushdown

  21. Witness language by two-way machine Initialize PD memory 4 ├ 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 q state TOP 0 0 X I pushdown

  22. Witness language by two-way machine Initialize PD memory 4 ├ 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 q TOP 0 state 0 0 X I pushdown

  23. Witness language by two-way machine Initialize PD memory 4 ├ 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  24. Witness language by two-way machine Initialize PD memory 4 ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 O(1) states 0 X I pushdown

  25. Witness language by two-way machine Left Part ? = Z ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  26. Witness language by two-way machine Left Part ? = Z ├ 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  27. Witness language by two-way machine Left Part ? = Z ├ 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 Difference q TOP 0 0 Z 0 0 X I pushdown

  28. Witness language by two-way machine Left Part ├ 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 q TOP 0 state Z 0 0 X I pushdown

  29. Witness language by two-way machine Left Part ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  30. Witness language by two-way machine Left Part ? = Z ├ 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  31. Witness language by two-way machine Left Part ? = Z ├ 0 1 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 Difference q TOP 0 0 Z 0 0 X I pushdown

  32. Witness language by two-way machine Left Part ├ 0 1 1 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 q TOP 0 state Z 0 0 X I pushdown

  33. Witness language by two-way machine Left Part ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  34. Witness language by two-way machine Left Part ? = Z ├ 1 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 Difference TOP 0 q 0 0 Z 0 0 X I pushdown

  35. Witness language by two-way machine Left Part ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  36. Witness language by two-way machine Left Part ├ $ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  37. Witness language by two-way machine Left Part . . . ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 0 state Z 0 0 X I pushdown

  38. Witness language by two-way machine Left Part ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z := Z + 1 0 0 X I pushdown

  39. Witness language by two-way machine Left Part ? = Z ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z 0 0 X I pushdown

  40. Witness language by two-way machine Left Part ? = Z ├ ┤ 0 1 0 0 ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 YES q 1 Z 0 0 X I pushdown

  41. Witness language by two-way machine Right Part ? Z= ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z 0 0 X I pushdown

  42. Witness language by two-way machine Right Part ? Z= ├ 0 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 TOP 0 q 1 state Z 0 0 X I pushdown

  43. Witness language by two-way machine Right Part ? Z= ├ 0 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 Difference q 1 TOP 1 Z 0 0 X I pushdown

  44. Witness language by two-way machine Right Part ├ 0 1 0 0 ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 q TOP 1 state Z 0 0 X I pushdown

  45. Witness language by two-way machine Right Part ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z 0 0 X I pushdown

  46. Witness language by two-way machine Right Part ? Z= ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z 0 0 X I pushdown

  47. Witness language by two-way machine Right Part ? Z= ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z 0 0 X I pushdown

  48. Witness language by two-way machine Right Part ? Z= ├ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 $ 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z 0 0 X I pushdown

  49. Witness language by two-way machine Right Part No match ├ $ ┤ ₵ ₵ ₵ ₵ ₵ ₵ ₵ 0 1 0 0 0 1 1 0 1 0 1 1 0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 TOP 0 q 1 state Z 0 0 X I pushdown

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

CS Seminar. Feb 09. Alexey Onufriev, Dept of Computer Science; Dept. of Physics and the GBCB

CS Seminar. Feb 09. Alexey Onufriev, Dept of Computer Science; Dept. of Physics and the GBCB

The computational Core of Molecular Modeling. (The What? Why? And How? ) CS Seminar. Feb 09. Alexey Onufriev, Dept of Computer Science; Dept. of Physics and the GBCB program. Thanks to: Faculty co-authors: T.M. Murali, M. Prisant, L.

647 views • 53 slides
a Dept of Computer Science, Michigan State University b Dept of Geography, Michigan State

a Dept of Computer Science, Michigan State University b Dept of Geography, Michigan State

CONTOUR REGRESSION: A distribution-regularized regression framework for climate modeling Zubin Abraham a , Pang-Ning Tan a , Julie A. Winkler b , Perdinan b , Shiyuan Zhong b , Malgorzata Liszewska c a Dept of Computer Science, Michigan State

811 views • 28 slides
Machine Learning for Survival Analysis Chandan K. Reddy Yan Li Dept. of Computer Science Dept.

Machine Learning for Survival Analysis Chandan K. Reddy Yan Li Dept. of Computer Science Dept.

Machine Learning for Survival Analysis Chandan K. Reddy Yan Li Dept. of Computer Science Dept. of Computational Medicine Virginia Tech and Bioinformatics http://www.cs.vt.edu/~reddy Univ. of Michigan, Ann Arbor 1 Tutorial Outline Basic

1.28k views • 107 slides
Psychovisual Enhancements Aaron Koehl Dept. of Physics, Computer Science, and Engineering

Psychovisual Enhancements Aaron Koehl Dept. of Physics, Computer Science, and Engineering

Enabling Optimization of Socially Sourced Images using Psychovisual Enhancements Aaron Koehl Dept. of Physics, Computer Science, and Engineering Christopher Newport University Haining Wang Dept. of Electrical and Computer Engineering

996 views • 53 slides
Craig Gentry IBM Watson Bar-Ilan University Dept. of Computer Science Optimizations of

Craig Gentry IBM Watson Bar-Ilan University Dept. of Computer Science Optimizations of

Winter School on Lattice-Based Cryptography and Applications Bar-Ilan University, Israel 19/2/2012-22/2/2012 Bar-Ilan University Dept. of Computer Science Craig Gentry IBM Watson Bar-Ilan University Dept. of Computer Science

1.08k views • 85 slides
Computer Graphics CS 543 Final Review Prof Emmanuel Agu Computer Science Dept. Worcester

Computer Graphics CS 543 Final Review Prof Emmanuel Agu Computer Science Dept. Worcester

Computer Graphics CS 543 Final Review Prof Emmanuel Agu Computer Science Dept. Worcester Polytechnic Institute (WPI) Exam Overview Tuesday, December 17, 2013 in class Midterm covered up to lecture 6 (Hierarchical 3D modeling)

621 views • 6 slides
Index Introduction Previous approaches Our proposal Evaluation Conclusions and future work J.

Index Introduction Previous approaches Our proposal Evaluation Conclusions and future work J.

C O L ES IR at CLEF 2007: from English to French via Character N -Grams Jes us Vilares Michael P. Oakes Manuel Vilares Computer Science Dept. School of Computing and Technology Computer Science Dept. University of A Coru na University

509 views • 31 slides
Computer Graphics (CS 543) Lecture 8c: Texturing Prof Emmanuel Agu Computer Science Dept.

Computer Graphics (CS 543) Lecture 8c: Texturing Prof Emmanuel Agu Computer Science Dept.

Computer Graphics (CS 543) Lecture 8c: Texturing Prof Emmanuel Agu Computer Science Dept. Worcester Polytechnic Institute (WPI) The Limits of Geometric Modeling Although graphics cards can render over 100 million polygons per second

750 views • 35 slides
Insider Problem and Elec1ons Ma3 Bishop Computer Security Lab Dept. of Computer Science

Insider Problem and Elec1ons Ma3 Bishop Computer Security Lab Dept. of Computer Science

Insider Problem and Elec1ons Ma3 Bishop Computer Security Lab Dept. of Computer Science University of California, Davis Ma3 Bishop, February 18, 2016 Slide #1 Opening Thought Theres no sense in being precise when you don't even know

810 views • 54 slides
Selected Topics of Theoretical Computer Science (456-335/1) Petr Jan car Dept of Computer

Selected Topics of Theoretical Computer Science (456-335/1) Petr Jan car Dept of Computer

Selected Topics of Theoretical Computer Science (456-335/1) Petr Jan car Dept of Computer Science Technical University Ostrava (FEI V SB-TU) www.cs.vsb.cz/jancar TU Ostrava, winter semester 2005/2006 Petr Jan car (TU Ostrava)

511 views • 24 slides
There is always room for one more, and for many more Aurora Ramrez Dept. Computer Science and

There is always room for one more, and for many more Aurora Ramrez Dept. Computer Science and

There is always room for one more, and for many more Aurora Ramrez Dept. Computer Science and Numerical Analysis University of Crdoba, Spain 1 st Int. Summer School in Search Based Software Engineering, Cdiz. 30 th June 2016 How many

424 views • 27 slides
Craig Gentry IBM Watson Bar-Ilan University Dept. of Computer Science Homomorphic Encryption

Craig Gentry IBM Watson Bar-Ilan University Dept. of Computer Science Homomorphic Encryption

Winter School on Lattice-Based Cryptography and Applications Bar-Ilan University, Israel 19/2/2012-22/2/2012 Bar-Ilan University Dept. of Computer Science Craig Gentry IBM Watson Bar-Ilan University Dept. of Computer Science Homomorphic

2.15k views • 113 slides
Security Across the Computer Science Curriculum L. Felipe Perrone perrone@bucknell.edu Dept. of

Security Across the Computer Science Curriculum L. Felipe Perrone perrone@bucknell.edu Dept. of

Security Across the Computer Science Curriculum L. Felipe Perrone perrone@bucknell.edu Dept. of Computer Science Bucknell University 1 SwA CBK Monterey, CA August 18, 2006 Security and Software Assurance in Computer Science Programs

289 views • 18 slides
Computer Graphics CS 543 Lecture 12 (Part 1) Curves Prof Emmanuel Agu Computer Science Dept.

Computer Graphics CS 543 Lecture 12 (Part 1) Curves Prof Emmanuel Agu Computer Science Dept.

Computer Graphics CS 543 Lecture 12 (Part 1) Curves Prof Emmanuel Agu Computer Science Dept. Worcester Polytechnic Institute (WPI) So Far Dealt with straight lines and flat surfaces Real world objects include curves Need to develop:

345 views • 34 slides
Computer Graphics 543 Lecture 2(Part 3): Fractals Prof Emmanuel Agu Computer Science Dept.

Computer Graphics 543 Lecture 2(Part 3): Fractals Prof Emmanuel Agu Computer Science Dept.

Computer Graphics 543 Lecture 2(Part 3): Fractals Prof Emmanuel Agu Computer Science Dept. Worcester Polytechnic Institute (WPI) What are Fractals? Mathematical expressions to generate pretty pictures Evaluate math functions to create

826 views • 38 slides
Meets Visualization Jaegul Choo Assistant Professor Dept. of Computer Science and Engineering

Meets Visualization Jaegul Choo Assistant Professor Dept. of Computer Science and Engineering

Big Data Visual Analytics: Machine Learning Meets Visualization Jaegul Choo Assistant Professor Dept. of Computer Science and Engineering Korea University About Me Google Jaegul Choo Assistant Professor at Computer Science dept. in

306 views • 28 slides
Deciding contractibility of curves on the boundary of a 3-manifold Eric Colin de Verdi` ere

Deciding contractibility of curves on the boundary of a 3-manifold Eric Colin de Verdi` ere

Deciding contractibility of curves on the boundary of a 3-manifold Eric Colin de Verdi` ere Salman Parsa CNRS, Universit e Paris-Est Marne-la-Vall ee Sharif University of Technology France Iran The problem Given solid obstacles

790 views • 74 slides
ADMIN SI232 Set #11: Fun with Floating Point (Chapter 3) 1 2 (blank space) Exercise #1

ADMIN SI232 Set #11: Fun with Floating Point (Chapter 3) 1 2 (blank space) Exercise #1

ADMIN SI232 Set #11: Fun with Floating Point (Chapter 3) 1 2 (blank space) Exercise #1 Represent +7.25 10 in binary single precision 31 30 29 28 27 26 25 24 23 22 21 20 . . . 9 8 7 6 5 4 3 2 1 0 3 (blank space)

377 views • 6 slides
16-bit Memory Word CSCI 125 & 161 / ENGR 144 To store number 6, use 0000000000000110

16-bit Memory Word CSCI 125 & 161 / ENGR 144 To store number 6, use 0000000000000110

16-bit Memory Word CSCI 125 & 161 / ENGR 144 To store number 6, use 0000000000000110 Lecture 5 Value 0 is 0000000000000000 Martin van Bommel Largest value is 1111111111111111 = 65,535 = 2 16 1 32-bit word gives

163 views • 3 slides
Hadwiger numbers of self-complementary graphs Elena Pavelescu University of South Alabama joint

Hadwiger numbers of self-complementary graphs Elena Pavelescu University of South Alabama joint

Hadwiger numbers of self-complementary graphs Hadwiger numbers of self-complementary graphs Elena Pavelescu University of South Alabama joint work with Andrei Pavelescu 31st Cumberland Conference University of Central Florida, 18-19 May 2019

173 views • 15 slides
Introduction to Algebraic Graph Transformation Fernando Orejas Royal Holloway University of

Introduction to Algebraic Graph Transformation Fernando Orejas Royal Holloway University of

Introduction to Algebraic Graph Transformation Fernando Orejas Royal Holloway University of London on leave from Universitat Politcnica de Catalunya, Barcelona Lecture 1: Basic Notions in Graph Transformation Lecture 2: Fundamental

1.33k views • 74 slides
The Erd os-Ko-Rado Theorem and the Treewidth of the Kneser Graph Daniel Harvey School of

The Erd os-Ko-Rado Theorem and the Treewidth of the Kneser Graph Daniel Harvey School of

The Erd os-Ko-Rado Theorem and the Treewidth of the Kneser Graph Daniel Harvey School of Mathematical Sciences, Monash University 7/7/14 1 Erd os-Ko-Rado Theorem 2 Separators 3 The Kneser Graph 4 Treewidth Erd os-Ko-Rado Theorem

761 views • 52 slides
Double Dose of Double-Negation Translations Olivier Hermant CRI, MINES ParisTech June 2, 2014

Double Dose of Double-Negation Translations Olivier Hermant CRI, MINES ParisTech June 2, 2014

Double Dose of Double-Negation Translations Olivier Hermant CRI, MINES ParisTech June 2, 2014 O. Hermant (Mines) Double Negations June 2, 2014 1 / 37 Double-Negation Translation: Five Ws The theory : automatic theorem proving: classical

1k views • 77 slides
Double Negation Translations as Morphisms Olivier Hermant CRI, MINES ParisTech December 1, 2014

Double Negation Translations as Morphisms Olivier Hermant CRI, MINES ParisTech December 1, 2014

Double Negation Translations as Morphisms Olivier Hermant CRI, MINES ParisTech December 1, 2014 UFRN, Natal O. Hermant (Mines) Double Negations December 1, 2014 1 / 24 Double-Negation Translations Double-Negation translations: a

360 views • 32 slides

More recommend