Digital Design - Digitális Technika

Practice - Gyakorlat

Timeline

  • 1. week -- Number Systems (slide)
  • 2. week -- Floating Point Numbers and Binary Codes (slide)
  • 3. week -- Logic Gates and Boolean Equations (slide)
  • 4. week -- Boolean Algebra (slide)
  • 5. week -- Karnaugh Map and Quine-McClusky Method (slide)
  • 6. week -- 1. Midterm
  • 7. week -- Logical Circuit Design (slide)
  • 8. week -- Spring Break
  • 9. week -- Combinational Circuits (slide)
  • 10. week -- Latches and Flip-Flops (slide)
  • 11. week -- Finite State Machines (slide)
  • 12. week -- 2. Midterm
  • 13. week -- Retake

Supplementary Materials

  • Introduction into the Digital Works simulator - slide
  • Digital circuit simulator - Digital works
  • Macro in Digital Works - Link
  • Digital exercise collection - Link

Literature

  • D.M. Harris, S.L. Harris, Digital Design and Computer Architecture, 2nd ed., Elsevier, 2013.
  • T.L. Floyd, Digital Fundamentals, 11th ed., Global Edition, Pearson, 2015.
  • C. Maxfield, Bebop to the Boolean Boogie. An Unconventional Guide to Electronics. 3rd ed., Elsevier, 2009

Időbeosztás

  • 1. hét -- Számrendszerek (slide)
  • 2. hét -- Lebegőpontos Számábrázolás és Bináris Kódok (slide)
  • 3. hét -- Logikai Kapuk és Boole Egyenletek (slide)
  • 4. hét -- Boole Algebra (slide)
  • 5. hét -- Karnaugh Tábla és a Quine-McClusky Módszer(slide)
  • 6. hét -- 1. ZH
  • 7. hét -- Logikai Áramkörök Tervezése (slide)
  • 8. hét -- Tavaszi Szünet
  • 9. hét -- Kombinációs Áramkörök (slide)
  • 10. hét -- Latchek és Flip-flopok (slide)
  • 11. hét -- Véges Állapotgépek (slide)
  • 12. hét -- 2. ZH
  • 13. hét -- Pót ZH

Kiegészítő anyagok

  • Bevezetés a Digital Works szimulátor használatába - slide
  • Digitális áramkör szimulátor - Digital works
  • Digital Works Makró - Link
  • Digitális példatár - Link

Szakirodalom

  • D.M. Harris, S.L. Harris, Digital Design and Computer Architecture, 2. kiadás, Elsevier, 2013.
  • T.L. Floyd, Digital Fundamentals, 11. kiadás, Global Edition, Pearson, 2015.
  • Göllei Attila, Holczinger Tibor, Vörösházi Zsolt. Digitalis technika I. Jegyzet, 2014.

Embedded Systems - Beágyazott Rendszerek

Lectures

  • 1. week -- General Overview of Computer Systems (slide)
  • 2. week -- Overview of Embedded Systems (slide)
  • 3. week -- Digital Building Blocks (slide)
  • 4. week -- ARM Architecture - Part 1. (slide)
  • 5. week -- ARM Architecture - Part 2. (slide)
  • 6. week -- ARM Machine Language (slide)
  • 7. week -- Microarchitecture - Single-Cycle (slide)
  • 8. week -- Break
  • 9. week -- Memory Hierarchy (slide)
  • 10. week -- IO System of BCM2835 (slide)
  • 11. week -- General IO Capabilities (slide)
  • 12. week -- Peripherals (slide)

Supplemetary Materials

  • ARM Immediate Value Encoding (Link)

Literature

  • S.L. Harris, D.M. Harris, Digital Design and Computer Architecture, ARM Edition. Elsevier, 2016.
  • D.A Patterson, J.L. Hennessy, Computer Organization and Design. Elsevier, 2017.
  • T. Noergaard, Embedded Systems Architecture. Elsevier, 2013.
  • M. Wolf, Computers as Components, 4th ed., Elsevier, 2017.

Laboratory

Evaluation Sheet

Youtube channel

  • Demonstration videos to some laboratory exercises (Link)

Supplemetary Materials

  • Raspberry Pi Projects (Link)
  • Adafruit Learn (Link)
  • Sparkfun Learn (Link)
  • Instructables Circuits (Link)
  • Electronics Tutorials (Link)
  • Digital Compass (Link1, Link2)
  • Troubleshooting (Link)

Literature

  • C. Platt, Make: Electronics, 2nd ed., Marker Media, 2015.
  • S. McManus, M. Cook, Raspberry Pi for Dummies, 3rd ed., Wiley, 2017.
  • S. Monk, Raspberry Pi Cookbook, 2nd edition, O’Reilly, 2016.

Programmable Logical Devices

Lectures

  • 1. week -- General Description of the Course
  • 2. week -- Overview of Programmable Logical Devices (slide)
  • 3. week -- Reconfigurable Computing - FPGA (slide)
  • 4. week -- FPGA Architecture (slide)
  • 5. week -- Programming Technologies (slide)
  • 6. week -- Design Flow - Simulation (slide)
  • 7. week -- Design Flow - Synthesis and Implementation (slide)
  • 8. week -- Verilog HDL (slide)
  • 9. week -- Break
  • 10. week -- Behavioral Modelling in Verilog (slide)
  • 11. week -- Modelling Finite State Machines (slide)
  • 12. week -- Processor Design (slide)
  • 13. week -- Exam
  • 14. week -- Retake

Supplemetary Materials

  • EPROM Cell Illustration (Link)

Literature

  • C.H. Roth, L.K. John, B.K. Lee, Digital Systems Design Using Verilog, 5th ed., Cangage Learning, 2016.
  • S.L. Harris, D.M. Harris, Digital Design and Computer Architecture, ARM Edition. Elsevier, 2016.
  • T. Floyd. Digital Fundamentals, 11th edition. Pearson, 2015.
  • C. Maxfield. FPGAs Instant Access. Newnes, 2008.
  • B.J. LaMeres. Introduction to Logic Circuits & Logic Design with Verilog. 2nd ed. Springer, 2019.

Laboratory

Evaluation Sheet

Supplemetary Materials

Literature

  • Xilinx University Program, https://www.xilinx.com/support/university.html, Accessed on 10/09/2020
  • D.M. Harris, S.L. Harris, Digital Design and Computer Architecture, 2nd ed., Elsevier, 2013
  • Michael D. Ciletti, Advanced Digital Design With the Verilog HDL, 2nd ed., Pearson, 2005

Data Science

Machine Learning

Timeline

  • Artificial Intelligence (link)
  • Introduction into Machine Learning (link)
  • The Pandas Library and Data Visualization (link)
  • K-nearest Neighbors(link)
  • Linear Regression (link)
  • Multivariate Linear Regression (link)
  • Logistic Regression (link)
  • Naive Bayes (link)
  • Decision Tree (link)
  • Ensemble (link)

Supplementary Materials

  • Jupyter Notebook (link)
  • Python Tutorial (link)
  • CSC2515, Introduction to Machine Learning (link)

Literature

  • A. Geron, Hands-On Machine Larning with Scikit-Learn and Tensorflow, 3rd Ed., O'Reilly Media, 2022.
  • V. Kotu, B. Deshpande, Data Science, 2nd Ed., Morgan Kaufmann, 2019.
  • A. Burkov, The Hundred-Page Machine Learning Book, 2019.
  • Jake VanderPlas, Python Data Science Handbook, O'Reilly Media, 2023.
  • C. M. Bishop, Pattern Recognition and Machine Learning. Link

Artificial Neural Networks

  • Neuron (link)
  • Artificial Neural Network (ANN) (link)
  • Training ANN (link)
  • Regularization (link)
  • ANN in Keras (link)

Supplementary Materials

  • NeuPy Link
  • CS231n, Convolutional Neural Networks for Visual Recognition Link
  • CS434a/541a, Pattern Recognition Link
  • CSC2515, Introduction to Machine Learning Link
  • CPSC540, Machine Learning Link

Literature

  • M. Nielsen, Neural Networks and Deep Learning, 2018. Link
  • M.T. Hagan, H.B. Demuth, M.H. Beale, O. De Jesus, Neural Network Design, 2.nd ed., 2014. Link

Ipar 4.0

Előadás Anyagok

  • Az Ipar 4.0 Technológia Háttere (link)
  • Beágyazott Rendszerek (link)
  • Tárgyak Internete (IoT)(link)
  • Adat (link)
  • Mesterséges Intelligencia (AI) (link)
  • Az AI Ipari Alkalmazásai (link)
  • Felügyelt tanulás (link)

Szakirodalom

  • ..

System Architectures

Lectures

  • 1. -- General Introduction (Rules and Requirements)
  • 2. -- Computer Technology (slide)
  • 3. -- Performance and Power consumption (slide)
  • 4. -- Embedded Systems (slide)
  • 5. -- Internet of Things (slide)
  • 5. -- Simple Programmable Logical Devices (slide)
  • 6. -- Filed Programmable Gate Arrays (slide)
  • 7. -- RISK-V Architecture (slide)

Supplemetary Materials

  • Khan Academy - Cryptography (link)
  • Literature

    • W. Stallings. Computer Organization and Architecture, 11th edition. Pearson, 2019.
    • J. McClellan, R. Schafer, M. Yoder, DSP First, 2nd edition. Pearson, 2015.
    • J.F. Kurose, K.W. Ross, Computer Networking A Top-Down Approach, 6th edition. Pearson, 2013.
    • S.L. Harris, D.M. Harris, Digital Design and Computer Architecture, ARM Edition. Elsevier, 2016.
    • T. Floyd. Digital Fundamentals, 11th edition. Pearson, 2015.
    Last update: March 01 2024 08:17:10.

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