Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Intelligent Embedded Systems Laboratory

    A tantárgy neve magyarul / Name of the subject in Hungarian: Intelligens beágyazott rendszerek laboratórium

    Last updated: 2024. március 1.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    MSc in Electrical Engineering
    Intelligent Embedded Systems specialization
    Course ID Semester Assessment Credit Tantárgyfélév
    VIMIMA21   0/0/3/f 5  
    3. Course coordinator and department Dr. Bank Balázs Lajos,
    4. Instructors Dr. Balázs Lajos Bank associate professor, MIT
    6. Pre-requisites
    Kötelező:
    NEM
    (TárgyEredmény( "BMEVIMIMA12", "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVIMIMA12", "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:
    Perception and signal processing
    7. Objectives, learning outcomes and obtained knowledge

    The aim of this laboratory course is to deepen the knowledge of the information processing algorithms found in embedded systems and to get acquainted with the corresponding software tools. During the measurements students will use elementary signal processing knowledge to create and test more complex systems. The majority of laboratory tasks are performed using real physical systems or the models of such systems.

    8. Synopsis

    1. Introduction to the capabilities and resources of the signal processing development environment available in the laboratory. General structure of signal processing programs, development and debugging steps.

    2. Design and implementation of digital filters: design, implementation, and measurement of various digital filters with different structures and specifications.

    3-4. Implementation of a complex signal processing task using a DSP development board: the task can be chosen freely from a list of example problems.

    5-6. Implementation of the LMS algorithm: Introduction to the variations of the LMS algorithm, examination of the XLMS algorithm. Implementation of adaptive echo cancellation in electronic and acoustic channels.

    7-8. Vibration analysis: Practicing the use of accelerometers, microphones and associated measurement equipment. The example application also includes a problem from the field of predictive maintenance.

    9-10. Implementation of an embedded data acquisition system: realization of data acquisition system built from embedded devices, capable of measuring analog signals, transmitting them and storing them in a database for further processing.

    9. Method of instruction Laboratory
    10. Assessment

    In order to pass the course, all the measurements should be accomplished with success, the reports handled in within the deadlines and each report should get at least a pass mark.

    11. Recaps

    Two measurements can be repeated during the semester.

    12. Consultations On request, upon agreement with the lecturers in advance.
    14. Required learning hours and assignment
    Contact hour 40
    Preparation for labs50
    Preparation for mid-term exam 
    Homework 
    Mastering selected written curriculum
    		20
    Preparation for lab reports
    		40
    Total150
    15. Syllabus prepared by

    Dr. Tamás Dabóczi professor, MIT
    Dr. György Orosz associate professor, MIT
    Dr. László Sujbert associate professor, MIT