MODULE DESCRIPTION Module code Module name Teoria sygnałów Module name in English Signal Theory Valid from academic year 01/013 MODULE PLACEMENT IN THE SYLLABUS Subject Level of education Studies profile Form and method of conducting Specialisation Unit conducting the module Module co-ordinator Electrical Engineering 1 st degree (1st degree / nd degree) General (general / practical) Full-time (full-time / part-time) Industrial Electronics and Power Engineering Electronics The Department of Power Engineering Electronics Andrzej Zawadzki, PhD, Eng. Approved by: MODULE OVERVIEW Type of subject/group of subjects Module status Language of conducting Module placement in the syllabus - semester Subject realisation in the academic year Initial requirements Examination Number of ECTS credit points 4 Major (basic / major / specialist subject / conjoint / other HES) Non-compulsory (compulsory / non-compulsory) Polish 6 th semester Summer semester (winter / summer) Circuit Theory 1 and, the Fundamentals of Electronics 1 (module codes / module names) No (yes / no) Method of conducting Lecture Classes Laboratory Project Other Per semester 30 30
TEACHING RESULTS AND THE METHODS OF ASSESSING TEACHING RESULTS Module target The aim of the module is to familiarise students with: the issues concerning signal and basic principles of processing them; signal representation methods in a frequency and correlation domain; discussing signals in functional space categories; applying the sampling operation, quantizing, and signal coding; signal filtering, and filter structure and design. Effect symbol Teaching results Teaching methods (/l/p/other) Reference to subject effects Reference to effects of a field of study W_03 A student has systematised basic knowledge (with theoretical background) as regards signals and basic principles of processing them. A student has detailed knowledge as regards signal representation, the behaviour of systems, analysing their responses to various types of signal types. K_W01 K_W0 K_W07 A student knows basic filter design methods. K_W06 K_W18 A student can make a frequency analysis of signals and system functioning; a student is also able to determine its responses to various types of input signals. A student is able to utilise the learnt methods to analyse the operation, design, modification, and control of system parameters. A student understands the necessity of continuous self-education. A student is aware of and correctly identifies the signals and methods of processing them. K_U09 K_U16 K_U11 K_U13 K_K01 K_K0 K_K03 T1A_W03 T1A_W04 T1A_W07 T1A_U09 T1A_U14 T1A_U15 T1A_U16 T1A_K01 T1A_K04 T1A_K05 Teaching contents: Teaching contents as regards lectures Lecture number Teaching contents 1 The elements of general signal theory. Signal division. Deterministic and random signals. One- and two-dimensional signals. The definition of signals with the use of elementary signals. The parameters of deterministic signals a mean and effective value. Complex signals. The distribution of signals into components. Signal power and energy. Basic issues occurring in digital signal processing. 3 Signal spaces, a norm, distance, and a scalar product. Signal orthogonality. Signal representations in finitely dimensional spaces. 4 Basic approximation issues. Linearly independent and orthogonal functions. Orthogonal expansion; function norms; quality approximation assessment. 5 Fourier series: trigonometric, polar, complex, and harmonic form (amplitude, frequency, and phase). 6 Fourier transform of periodical and non-periodical signals. Fourier transform and series relationship. Signal spectrums. 7/8 Continuous signal discretisation. Signal sampling; the concept of a sampling function; the spectrum of a sampled signal. Shannon s theorem. Reference to teaching results for a module
9 Signal reconstruction based on its samples. The selected sampling issues concerning a discrete signal. 10 Discrete Fourier transform (DFT): its definition, properties, physical interpretation; the relationship between DPF with an integral Fourier transform. Fast Fourier transform (FFT). 11/1 Digital signals. Z-transform of discrete signals: its definition, properties, and examples. Inverse Z transform. 13 Analogue signal processing through linear filters. Analogue filters; a description in time, complex, and frequency domains. Discrete signal filters described with differential equations. 14 Finite impulse response filters: their definition, linearity, and frequency characteristics. Filters with non-finite impulse response: frequency characteristics and their interpretation. 15 Obtaining a credit for the lectures. Teaching contents as regards Class number Teaching contents Reference to teaching results for a module 1, Continuous signals in time. Fourier series. Fourier transform. 3 DFT; FFT algorithms. 4 Inverse Fourier transform. 5,6 Sampling and quantisation. 7,8 Digital signals. Z transform and inverse Z transform. 9.10 Digital system description. Solving differential equations. 11/1 Linear signal processing. Filters. 13/14 Analogue filters, the distribution of zeros and poles on a complex s plane; Butterworth, Chebyshev, and Cauer approximations. 15 Obtaining a credit for the. The methods of assessing teaching results Effect symbol W_03 Methods of assessing teaching results (assessment method, including skills reference to a particular project, laboratory assignments, etc.) A practical test during laboratory A practical test during laboratory A written test conducted during the lectures and laboratory A practical test during laboratory
STUDENT S INPUT ECTS credit points Type of student s activity Student s workload 1 Participation in lectures 30 Participation in 30 3 Participation in laboratories 4 Participation in tutorials (-3 times per semester) 5 Participation in project 6 Project tutorials 7 Participation in an examination 8 9 Number of hours requiring a lecturer s assistance 60 (sum) 10 Number of ECTS credit points which are allocated for assisted work 11 Unassisted study of lecture subjects 5 1 Unassisted preparation for 0 13 Unassisted preparation for tests 10 14 Unassisted preparation for laboratories 15 Preparing reports 16 Preparing for a final laboratory test 17 Preparing a project or documentation 18 Preparing for an examination 5 19 Preparing questionnaires 0 Number of hours of a student s unassisted work 60 (sum) 1 Number of ECTS credit points which a student receives for unassisted work Total number of hours of a student s work 10 3 ECTS credit points per module 1 ECTS credit point=5-30 hours 4 4 Work input connected with practical Total number of hours connected with practical 60 5 Number of ECTS credit points which a student receives for practical