| Language of instruction : English |
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Sequentiality
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Advising sequentiality bound on the level of programme components
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Following programme components are advised to also be included in your study programme up till now.
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Feedback and control systems (4295)
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4.0 stptn |
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| Degree programme | | Study hours | Credits | P2 SBU | P2 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 3rd year Bachelor of Engineering Technology - Electronics and ICT Engineering Technology | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
| 3rd year Bachelor of Engineering Technology - Nuclear Engineering Technology | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| EC1 - The holder of the degree possesses general scientific and technological application-oriented knowledge of the basic concepts, structures and coherence of the specific domain. | | | - DC
| EA 1.8 The student knows the basic theory of digital signals and systems. | | | | - BC
| The student is familiar with the concepts and techniques for the representation and processing of the discrete-time signals and systems. | - EC
| EC2 - The holder of the degree possesses general scientific and discipline-related engineering-technical insight in the basic concepts, methods, conceptual frameworks and interdependent relations of the specific domain. | | | - DC
| EA 2.7 The student has a deep understanding in digital filters. | | | | - BC
| The student has a deep understanding of the purpose and structure of the digital filters. | - EC
| EC5 - The holder of the degree can analyse unknown, domain-specific problems, subdivide them, structure them logically, determine the preconditions and interpret the data scientifically. | | | - DC
| EA 5.5 The student can analyse the discrete signals and LSI systems. | | | | - BC
| The student can efficiently analyse the discrete sequences and systems using the Fourier and Z transform. | - EC
| EC6 - The holder of the degree can select and use adequate solution methods to solve unknown, domain-specific problems and can work methodologically and make solid design choices. | | | - DC
| EA 6.6 The student can select and design an appropriate digital filter. | | | | - BC
| The student can design the FIR and IRR digital filters. | - EC
| EC7 - The holder of the degree can use the selected methods and tools innovatively to systematically implement domain-specific solutions and designs while being aware of practical and economic conditions and company-related implications. | | | - DC
| EA 7.5 The student can implement the solution algorithms in a computational framework. | | | | - BC
| The student can use matlab for digital signal processing. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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Signal processing plays an important role in a broad range of engineering systems where sampling, processing, presentation and storage of data is relevant. This course aims to provide a solid understanding of digital signal processing fundamentals and techniques such as the design and analysis of the analog and digital filters and signal transformations between the time and frequency domains.
During this course, the basic knowledge and experience will be built in the following main topics:
- Discrete-time signals and systems
- Convolution, modulation, sampling, Fourier and Z- transform
- Digital filters
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Period 2 Credits 4,00
| Evaluation method | |
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| Written evaluaton during teaching periode | 30 % |
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| Transfer of partial marks within the academic year | ✔ |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory course material |
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TOLEDO will be used for the communication with the students with respect to the home-works ,assignments, and study materials. |
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| Recommended reading |
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- Digital Signal Processing using Matlab,Vinay K. Ingle,9780495073116
- Digital signal processing, principles, algorithms, and applications,John G. Proakis et al.,9780029463789
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| Remarks |
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Relationship with research
This course provides students with a series of general analytical tools that are beneficial to a broad range of research from applied engineering and data science to physics/chemistry. Therefore, the concepts are presented in a way independent of a specific field of research but rather examples are discussed from different domains to demonstrate the potential applications.
Situation of the course in the curriculum
The digital signal processing field has interfaces with electronics (AD-DA converters, amplifiers, filters), electronic designs and measuring systems.
Inflow Relationship with other courses
This course builds on prior knowledge from system theory (e.g. Laplace transform, Fourier transform), mathematics (complex arithmetic), control engineering (e.g. feedback, Z transform) and electronics (electronic components)
Relationship with the professional field
Knowledge from the field of digital signal processing is useful among others in the electronic industry, in the automation sector (filters), multimedia world (signal processing, audio, image), and communication and telephone sectors. |
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| Bridging programme Electronics and ICT Engineering Technology - part 1 | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| Bridging programme Software Systems Engineering Technology - part 2 | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| Bridging programme Nuclear Engineering Technology - common part 2 | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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Signal processing plays an important role in a broad range of engineering systems where sampling, processing, presentation and storage of data is relevant. This course aims to provide a solid understanding of digital signal processing fundamentals and techniques such as the design and analysis of the analog and digital filters and signal transformations between the time and frequency domains.
During this course, the basic knowledge and experience will be built in the following main topics:
- Discrete-time signals and systems
- Convolution, modulation, sampling, Fourier and Z- transform
- Digital filters
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Period 2 Credits 4,00
| Evaluation method | |
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| Written evaluaton during teaching periode | 30 % |
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| Transfer of partial marks within the academic year | ✔ |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
TOLEDO will be used for the communication with the students with respect to the home-works ,assignments, and study materials. |
|
|
| Recommended reading |
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- Digital Signal Processing using Matlab,Vinay K. Ingle,9780495073116
- Digital signal processing, principles, algorithms, and applications,John G. Proakis et al.,9780029463789
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| Remarks |
| |
Relationship with research
This course provides students with a series of general analytical tools that are beneficial to a broad range of research from applied engineering and data science to physics/chemistry. Therefore, the concepts are presented in a way independent of a specific field of research but rather examples are discussed from different domains to demonstrate the potential applications.
Situation of the course in the curriculum
The digital signal processing field has interfaces with electronics (AD-DA converters, amplifiers, filters), electronic designs and measuring systems.
Inflow Relationship with other courses
This course builds on prior knowledge from system theory (e.g. Laplace transform, Fourier transform), mathematics (complex arithmetic), control engineering (e.g. feedback, Z transform) and electronics (electronic components)
Relationship with the professional field
Knowledge from the field of digital signal processing is useful among others in the electronic industry, in the automation sector (filters), multimedia world (signal processing, audio, image), and communication and telephone sectors. |
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| Preparation Programme Nuclear Engineering Technology - Environmental Engineering Technology | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| Preparation Programme Nuclear Engineering Technology - Nuclear and Medical Engineering Technology | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| |
|
|
Signal processing plays an important role in a broad range of engineering systems where sampling, processing, presentation and storage of data is relevant. This course aims to provide a solid understanding of digital signal processing fundamentals and techniques such as the design and analysis of the analog and digital filters and signal transformations between the time and frequency domains.
During this course, the basic knowledge and experience will be built in the following main topics:
- Discrete-time signals and systems
- Convolution, modulation, sampling, Fourier and Z- transform
- Digital filters
|
|
|
Period 2 Credits 4,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 30 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
|
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
TOLEDO will be used for the communication with the students with respect to the home-works ,assignments, and study materials. |
|
|
| Recommended reading |
| |
- Digital Signal Processing using Matlab,Vinay K. Ingle,9780495073116
- Digital signal processing, principles, algorithms, and applications,John G. Proakis et al.,9780029463789
|
|
|
| Remarks |
| |
Relationship with research
This course provides students with a series of general analytical tools that are beneficial to a broad range of research from applied engineering and data science to physics/chemistry. Therefore, the concepts are presented in a way independent of a specific field of research but rather examples are discussed from different domains to demonstrate the potential applications.
Situation of the course in the curriculum
The digital signal processing field has interfaces with electronics (AD-DA converters, amplifiers, filters), electronic designs and measuring systems.
Inflow Relationship with other courses
This course builds on prior knowledge from system theory (e.g. Laplace transform, Fourier transform), mathematics (complex arithmetic), control engineering (e.g. feedback, Z transform) and electronics (electronic components)
Relationship with the professional field
Knowledge from the field of digital signal processing is useful among others in the electronic industry, in the automation sector (filters), multimedia world (signal processing, audio, image), and communication and telephone sectors. |
|
|
|
|
|
| Exchange Programme Engineering Technology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
|
| |
|
|
Signal processing plays an important role in a broad range of engineering systems where sampling, processing, presentation and storage of data is relevant. This course aims to provide a solid understanding of digital signal processing fundamentals and techniques such as the design and analysis of the analog and digital filters and signal transformations between the time and frequency domains.
During this course, the basic knowledge and experience will be built in the following main topics:
- Discrete-time signals and systems
- Convolution, modulation, sampling, Fourier and Z- transform
- Digital filters
|
|
|
Period 2 Credits 4,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 30 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
|
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
TOLEDO will be used for the communication with the students with respect to the home-works ,assignments, and study materials. |
|
|
| Recommended reading |
| |
- Digital Signal Processing using Matlab,Vinay K. Ingle,9780495073116
- Digital signal processing, principles, algorithms, and applications,John G. Proakis et al.,9780029463789
|
|
|
| Remarks |
| |
Relationship with research
This course provides students with a series of general analytical tools that are beneficial to a broad range of research from applied engineering and data science to physics/chemistry. Therefore, the concepts are presented in a way independent of a specific field of research but rather examples are discussed from different domains to demonstrate the potential applications.
Situation of the course in the curriculum
The digital signal processing field has interfaces with electronics (AD-DA converters, amplifiers, filters), electronic designs and measuring systems.
Inflow Relationship with other courses
This course builds on prior knowledge from system theory (e.g. Laplace transform, Fourier transform), mathematics (complex arithmetic), control engineering (e.g. feedback, Z transform) and electronics (electronic components)
Relationship with the professional field
Knowledge from the field of digital signal processing is useful among others in the electronic industry, in the automation sector (filters), multimedia world (signal processing, audio, image), and communication and telephone sectors. |
|
|
|
|
|
| 3rd year Bachelor of Engineering Technology - Software Systems Engineering Technology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| EC1 - The holder of the degree possesses general scientific and technological application-oriented knowledge of the basic concepts, structures and coherence of the specific domain. | | | - DC
| EA 1.8 The student knows the basic theory of digital signals and systems. | | | | - BC
| The student is familiar with the concepts and techniques for the representation and processing of the discrete-time signals and systems. | - EC
| EC2 - The holder of the degree possesses general scientific and discipline-related engineering-technical insight in the basic concepts, methods, conceptual frameworks and interdependent relations of the specific domain. | | | - DC
| EA 2.7 The student has a deep understanding in digital filters. | | | | - BC
| The student has a deep understanding of the purpose and structure of the digital filters. | - EC
| EC5 - The holder of the degree can analyse unknown, domain-specific problems, subdivide them, structure them logically, determine the preconditions and interpret the data scientifically. | | | - DC
| EA 5.5 The student can analyse the discrete signals and LSI systems. | | | | - BC
| The student can efficiently analyse the discrete sequences and systems using the Fourier and Z transform. | - EC
| EC6 - The holder of the degree can select and use adequate solution methods to solve unknown, domain-specific problems and can work methodologically and make solid design choices. | | | - DC
| EA 6.6 The student can select and design an appropriate digital filter. | | | | - BC
| The student can design the FIR and IRR digital filters. | - EC
| EC7 - The holder of the degree can use the selected methods and tools innovatively to systematically implement domain-specific solutions and designs while being aware of practical and economic conditions and company-related implications. | | | - DC
| EA 7.5 The student can implement the solution algorithms in a computational framework. | | | | - BC
| The student can design the FIR and IRR digital filters. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
Signal processing plays an important role in a broad range of engineering systems where sampling, processing, presentation and storage of data is relevant. This course aims to provide a solid understanding of digital signal processing fundamentals and techniques such as the design and analysis of the analog and digital filters and signal transformations between the time and frequency domains.
During this course, the basic knowledge and experience will be built in the following main topics:
- Discrete-time signals and systems
- Convolution, modulation, sampling, Fourier and Z- transform
- Digital filters
|
|
|
Period 2 Credits 4,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 30 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
|
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
TOLEDO will be used for the communication with the students with respect to the home-works ,assignments, and study materials. |
|
|
| Recommended reading |
| |
- Digital Signal Processing using Matlab,Vinay K. Ingle,9780495073116
- Digital signal processing, principles, algorithms, and applications,John G. Proakis et al.,9780029463789
|
|
|
| Remarks |
| |
Relationship with research
This course provides students with a series of general analytical tools that are beneficial to a broad range of research from applied engineering and data science to physics/chemistry. Therefore, the concepts are presented in a way independent of a specific field of research but rather examples are discussed from different domains to demonstrate the potential applications.
Situation of the course in the curriculum
The digital signal processing field has interfaces with electronics (AD-DA converters, amplifiers, filters), electronic designs and measuring systems.
Inflow Relationship with other courses
This course builds on prior knowledge from system theory (e.g. Laplace transform, Fourier transform), mathematics (complex arithmetic), control engineering (e.g. feedback, Z transform) and electronics (electronic components)
Relationship with the professional field
Knowledge from the field of digital signal processing is useful among others in the electronic industry, in the automation sector (filters), multimedia world (signal processing, audio, image), and communication and telephone sectors. |
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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