K-INFO
HU
EN
Login

Intelligent Embedded Systems Laboratory

Intelligens beágyazott rendszerek laboratórium
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
Intelligens beágyazott rendszerek laboratórium
Intelligent Embedded Systems Laboratory
Subject code BMEVIMIMA21
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 0 0 3
type (linked/independent) autonomous course
Assessment type félévközi érdemjegy
Credits 5
Subject coordinator
Bank Balázs Lajos
position: egyetemi docens
Responsible department
Mesterséges Intelligencia és Rendszertervezés Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme

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.

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.

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

Laboratory

Tanulástámogató anyagok

Not provided.

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
nincs
General rules
Requirements: 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. Additional possibilities: Two measurements can be repeated during the semester.
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses
Perception and signal processing
Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.