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Course Description Course Name : Digital Signal Processing Course Code : EE-685 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. SAMİ ARICA Learning Outcomes of the Course : Describes and analyzes discrete time signals in the time domain and frequency domain. Applies digital signal processing techniques to analyze discrete time signals and systems. Applies digital signal processing techniques to design discrete time systems. Designs and applies digital filters. Designs and applies adaptive filters. Estimates power spectrum of a signal. Obtains time-frequency map of a signal. Understands multirate filter bank. Explains wavelet transform. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : Upon completion of this course students should be able to analyze signals and systems, and design systems employing digital signal processing techniques. Course Contents : Sampling and sampling theorem. Quantization. AD and DA conversion. Basic discrete-time signals. Discrete-time systems. Linear time invariant systems. Impulse response. Convolution sum. Random signals. Statistical properties of signals. Fourier series and Fourier transform. z-transform. Analysis of LTI systems in transform domain. Frequency response. System response. Magnitude and phase spectra. Power spectrum. Time-frequency distributions. Finite-Length Discrete Transforms. Filters. Linear phase filters. FIR filter design by Fourier series. Least-squares frequency domain design. s-to-z transform. Bilinear transform. Frequency warping. IIR filter design via s-to-z transform. Analysis of Finite Wordlength Effects. Adaptive Filters. Wiener, LMS, RLS filters. Forward prediction, backward prediction filters. Multirate Filter Banks and Wavelets. Multirate Digital Signal Processing Fundamentals. DSP Algorithm Implementation. Digital signal processors. Applications of Digital Signal Processing. Language of Instruction : Turkish Work Place : Department of Electrical and Electronics engineering building classrooms.   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Sampling and sampling theorem. Quantization. AD and DA conversion. Basic discrete-time signals. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 2 Discrete-time systems. Linear time invariant systems. Impulse response. Convolution sum. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 3 Ramdom signals. Statistical properties of signals. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 4 Fourier series and Fourier transform. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 5 The z-transform. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 6 Analysis of LTI systems in transform domain. Frequency response. System response. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 7 Magnitude and phase spectra. Power spectrum. Time-frequency distributions. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 8 Midterm exam. Textbook reading/Problem solving. written exam 9 Finite-Length Discrete Transforms. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 10 Filters. Linear phase filters. FIR filter design by Fourier series. Least-squares frequency domain design. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 11 s-to-z transform. Bilinear transform. Frequency warping. IIR filter design via s-to-z transform. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 12 Analysis of Finite Wordlength Effects. Adaptive Filters. Wiener, LMS, RLS filters. Forward predction, backward prediction filters. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 13 Multirate Filter Banks and Wavelets. Multirate Digital Signal Processing Fundamentals. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 14 DSP Algorithm Implementation. Digital signal processors. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 15 Applications of Digital Signal Processing. Textbook reading/Problem solving/Computer application. Lecture/Computer application. 16/17 Final exam. Textbook reading/Problem solving. written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  J. G. Proakis, D. G. Manolakis: Digital Signal Processing: Principles, Algorithms, and Applications, Prentice Hall, 1996.  S. K. Mitra: Digital Signal Processing: A Computer-Based Approach, McGraw Hill Higher Education, 2000.  A. V. Oppenheim, R. W. Schafer: Discrete-time signal processing, Prentice Hall, 1999.  M. H. Hayes: Statistical Signal Processing and Modeling, John Wiley and Sons, 1996. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 50     Homeworks/Projects/Others 12 50 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Communicates with people in an appropriate language and style. 1 2 Specializes by furthering his knowledge level at least in one of the basic subfields of electiral-electronic engineering. 5 3 Grasps the integrity formed by the topics involved in the field of specialization. 5 4 Grasps and follows the existing literature in the field of specialization. 4 5 Comprehends the interdisciplinary interaction of his field with other fields. 4 6 Has the aptitude to pursue theoretical and experimental work. 4 7 Forms a scientific text by compiling the knowledge obtained from research. 3 8 Works in a programmed manner within the framework set by the advisor on the thesis topic, in accordance with the logical integrity required by this topic. 5 9 Performs a literature search in scientific databases; in particular, to scan the databases in an appropriate manner, to list and categorize the listed items. 5 10 Has English capability at a level adequate to read and understand a scientific text in his field of specialization, written in English. 3 11 Compiles his/her knowledge in his/her field of specialization. in a presentation format, and presents in a clear and effective way. 3 12 Writes a computer code aimed at a specific purpose, in general, and related with his/her field of specialization, in particular 4 13 Pursues research ın new topics based on his/her existing research experıence. 2 14 Gives guidance in environments where problems related with his/her field need to be solved, and takes initiative. 2 15 Develops and evaluates projects, policies and processes in his field of specialization. 2 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 16 3 48 Assesment Related Works     Homeworks, Projects, Others 12 4 48     Mid-term Exams (Written, Oral, etc.) 1 2 2     Final Exam 1 2 2 Total Workload: 142 Total Workload / 25 (h): 5.68 ECTS Credit: 6