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  • Course Information
    • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Signal Processing Applications BİL496 FALL-SPRING 2+0 E 4
    Learning Outcomes
    1-recognize basic signal processing problems.
    2-model a problem he / she meets appropriately.
    3-know which method can solve the problem, advantages and disadvantages of different methods.
    4-apply the techniques learned in the course to the projects.
    5-have knowledge to understand current signal processing algorithms.
    6-use discrete-time systems design and interpretation skills.
    7-comment on real-time system design algorithms.
    8-gain the ability to model and execute ideas about the system before performing the system.
  • ECTS / WORKLOAD
    • ActivityPercentage

    (100)

    		NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14798
    Assignments0000
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)3011010
    Project3011010
    Laboratory 0000
    Final exam (exam + preparation) 4011212
    Other 0000
    Total Workload (hours)   172
    Total Workload (hours) / 30 (s)     5,73 ---- (6)
    ECTS Credit   4
  • Course Content
    • Week Topics Study Metarials
    1 Signal Processing and digital signal processing methods
    2 Discrete-time signals and their creation, sampling theorem, properties
    3 Discrete-time systems, comparison of these systems with continuous-time systems
    4 Real-time Signal Processing, Properties of Digital Signal Processors
    5 Formulating equations that model discrete-time systems
    6 Analytical solution methods of difference equations. MATLAB applications
    7 Z-transform analysis of signals and systems, transfer function. MATLAB applications
    8 Zero / polar representation, inverse z-transform, frequency response of systems
    9 Discrete-time Fourier transform
    10 Fast Fourier Transform. MATLAB applications
    11 Introduction to digital filters
    12 FIR filter design steps. MATLAB applications
    13 IIR filter design steps. MATLAB applications
    14 MATLAB applications
    Prerequisites -
    Language of Instruction Turkish
    Responsible Assist. Prof. Dr. Seda ŞAHİN
    Instructors -
    Assistants -
    Resources 1. Oppenheim, A.V. ve Schafer , R.W. ,Discrete-Time Signal Processing, Pearson, 2010. 2. Prof.Dr. Veysel Silindir v.d,Sinyaller ve Sistemler, Nobel dağıtım- Ankara-2001. 3.Emanuel C. Ifeachor, v.d. Digital signal Processing A Practical Approach, Addıson-wesly- 1994 .
    Supplementary Book -
    Goals to teach the basic mathematical analysis and signal processing methods used in digital signal processing applications, processing of signals in both time and frequency domain.
    Content Signal Processing and digital signal processing methods, Discrete-time signals and their creation, sampling theorem, properties, Discrete-time systems, comparison of these systems with continuous-time systems, Real-time Signal Processing, Properties of Digital Signal Processors, Formulating equations that model discrete-time systems, Analytical solution methods of difference equations. MATLAB applications, Z-transform analysis of signals and systems, transfer function. MATLAB applications, Zero / polar representation, inverse z-transform, frequency response of systems, Discrete-time Fourier transform, Fast Fourier Transform. MATLAB applications, Introduction to digital filters, FIR filter design steps. MATLAB applications, IIR filter design steps. MATLAB applications, MATLAB applications
  • Program Learning Outcomes
    • Program Learning Outcomes Level of Contribution
    1 To be able to apply mathematics, science and engineering theories and principles to Computer Engineering problems. 5
    2 To have the ability to define, model, and solve problems related to Computer Engineering. 4
    3 To be able to design and conduct experiments, as well as to analyze and interpret data. 4
    4 To be able to design and analyze a process for a specific purpose within technical and economical limitations. 4
    5 To be able to use modern techniques and calculation tools required for engineering applications. 4
    6 To have the awareness of professional liabilities and ethics. -
    7 To be able to get involved in interdisciplined and multidisciplined team work. 3
    8 To be able to declare his/her opinions orally or written in a clear, concise and brief manner. -
    9 To improve him/herself by following the developments in science, technology, modern issues, and know the importance of lifelong learning. 3
    10 To be able to evaluate engineering solutions for the global and social problems especially for the health, safety, and environmental problems. -
    11 To have knowledge about of contemporary issues. 3
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