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Detection and Estimation of Signals, 6 credits
Detektion och estimering av signaler, 6 hp
TSKS15
Main field of study
Electrical EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Erik G. LarssonDirector of studies or equivalent
Klas NordbergEducation components
Preliminary scheduled hours: 88 hRecommended self-study hours: 72 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
Main field of study
Electrical EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Applied Physics and Electrical Engineering, M Sc in Engineering
- Information Technology, M Sc in Engineering
- Computer Science and Engineering, M Sc in Engineering
- Industrial Engineering and Management, M Sc in Engineering
- Industrial Engineering and Management - International, M Sc in Engineering
- Communication Systems, Master's Programme
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Mathematics, Master's programme
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Linear algebra, probability theory, and a course similar to Signals, Information and Communications.
Intended learning outcomes
After completed course the student should
- with adequate terminology, in a well-structured manner and logically coherent, be able to describe and conduct simpler calculations that relate to classical and Bayesian estimation and detection theory, specifically the Neyman-Pearson theorem, error probabilities, decision regions, maximum-likelihood, linear and nonlinear models, Fisher information, Cramer-Rao bound, circularly symmetric noise, noise whitening, MMSE and LMMSE, GLRT, model order selection, coherent and non-coherent detection, composite hypothesis testing, nuisance parameters and basis expansions of waveforms in continuous time
- be able to describe, apply and implement in a conventional programming language, and show engineering understanding, for the theory and models used in the course
- be able to report work in written and oral form, using adequate language, terminology, structure and typography.
Course content
Binary hypothesis tests, Neyman-Pearson theorem, error probability. M-ary detection problems. Bayes cost, minimum probability of error. Nuisance parameters. Classical estimation: Maximum-likeihood. Cramer-Rao bound, Slepian-Bang's formula, efficiency. Linear, vector-valued models with Gaussian noise. Non-linear models. Noise whitening, complex-valued data, Gaussian noise, circularly symmetric noise. Bayesian estimation: MMSE and LMMSE. Composite hypothesis testing: GLRT and Bayesian approach, model selection. Finite-dimensional basis expansions of waveforms. Performance calculations: union bound, asymptotic properties of estimators. Applications to amplitude and phase estimation, frequency estimation, angle-of-arrival estimation, time-of-arrival estimation, source localization, coherent and non-coherent detection of waveforms.
Teaching and working methods
Lectures, problem classes and computer laboratory work. Written (individual) reports of laboratory work.
Examination
| LAB1 | Laboratory work | 2 credits | U, G |
| TEN1 | Written examination | 4 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för systemteknikDirector of Studies or equivalent
Klas NordbergExaminer
Erik G. LarssonCourse website and other links
http://www.commsys.isy.liu.se/en/student/AkurserEducation components
Preliminary scheduled hours: 88 hRecommended self-study hours: 72 h
Course literature
Additional literature
Books
- Kay, S, Statistical Signal Processing: Estimation Theory och Statistical Signal Processing: Detection Theory Prentice‐Hall
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| LAB1 | Laboratory work | 2 credits | U, G |
| TEN1 | Written examination | 4 credits | U, 3, 4, 5 |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Additional literature
Books
Kay, S, Statistical Signal Processing: Estimation Theory och Statistical Signal Processing: Detection Theory Prentice‐Hall
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
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| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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| 1.2 Fundamental engineering knowledge (G1X level) |
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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| 2.2 Experimentation, investigation, and knowledge discovery |
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| 2.3 System thinking |
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| 2.4 Attitudes, thought, and learning |
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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| 3.2 Communications |
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| 3.3 Communication in foreign languages |
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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| 4.4 Designing |
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| 4.5 Implementing |
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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