Applied Computer Systems Laboratory 2

A tantárgy neve magyarul / Name of the subject in Hungarian: Rendszer- és alkalmazástechnika labor 2

Last updated: 2019. január 19.

Budapest University of Technology and Economics
Faculty of Electrical Engineering and Informatics
Electrical Engineering M.Sc.         
Computer Based Systems Major Specialization         
Course ID Semester Assessment Credit Tantárgyfélév
VIAUMB03 3 0/0/3/f 4  
3. Course coordinator and department Dr. Vajk István,
4. Instructors

Name:

Title:

Department.:

Dr. György Orosz

assoc. professor

Measurement and Information Systems

Dr. László Blázovics

senior lecturer

Automation and Applied Informatics

5. Required knowledge –
6. Pre-requisites
Kötelező:
Only those student can register to the course who accomplished the Development of Software Applications (VIAUMA09) course.
(Training.Code=("5N-M7") ÉS
TárgyEredmény( "BMEVIAUMA09" , "jegy" , _ ) >= 2
ÉS
TárgyEredmény( "BMEVIAUMA10" , "jegy" , _ ) >= 2
ÉS NEM ( TárgyEredmény( "BMEVIAUM315" , "jegy" , _ ) >= 2
VAGY
TárgyEredmény("BMEVIAUM315", "FELVETEL", AktualisFelev()) > 0))

VAGY

(Training.Code=("5NAM7") ÉS
TárgyEredmény( "BMEVIAUMA09" , "jegy" , _ ) >= 2
ÉS NEM ( TárgyEredmény( "BMEVIAUM315" , "jegy" , _ ) >= 2
VAGY
TárgyEredmény("BMEVIAUM315", "FELVETEL", AktualisFelev()) > 0))

ÉS
NEM
(TárgyEredmény( "BMEVIAUMB05", "jegy" , _ ) >= 2
VAGY
TárgyEredmény("BMEVIAUMB05", "FELVETEL", AktualisFelev()) > 0)

A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

A kötelező előtanulmányi rend az adott szak honlapján és képzési programjában található.

Ajánlott:
–
7. Objectives, learning outcomes and obtained knowledge The aim of this course is to provide students with overview of application development process in a modern C++ development environment (Qt/QML) and also in the field of neural networks.
8. Synopsis Lab Topic
  1. Practical exercises of the git version control system. Creating remote and local repositories, branches, commits and manipulating them.
  2. Qt-C++ basics. Understanding the development process of the Qt ecosystem. Creating small example applications.
  3. Creating QML based user interfaces. Understanding and practicing the declarative UI paradigm.
  4. Complex Qt-QML exercises. Creating interactive hybrid C++-QML applications.
  5. Classification with multi-stage processing. Processing of vibration and sound signals using time- and frequency-domain methods, classification based on fuzzy systems and neural networks.
  6. Complex exercises in the topic of classification based on fuzzy systems and neural networks.
9. Method of instruction The course consists of 6 laboratory exercises (4 hours/session)
10. Assessment
In lecture term:
6 laboratory exercises
In examination period:
none
Pre-exam:none

The credits can be obtained by successfully participating on the laboratory exercises The final grade is calculated based on the grades of laboratory exercises, which are counted from quick tests, in class results and submitted documentation.
11. Recaps One laboratory exercise can be repeated during the semester and the repeat period in accordance with the Code of Studies and Exams (CSE).
12. Consultations Upon request, appointed with the laboratory instructors.
13. References, textbooks and resources Laboratory guides on the department website.
14. Required learning hours and assignment
Contact hours 24
Preparation for laboratory exercises 96
Total
 120
15. Syllabus prepared by

Name:

Title:

Department.:

Dr. Gábor Tevesz

assoc. professor

Automation and Applied Informatics

Dr. László Sujbert

assoc. professor

Measurement and Information Systems