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| ISTL7031 | Statistical Audio Processing | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | DEPARTMENT of STATISTICS and COMPUTER SCIENCES | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Orhan KESEMEN | | Co-Lecturer | None | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To teach statistical processing of audio on a computer. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | To learn audio processing techniques.
| 7,8 | 1,3 | | PO - 2 : | To learn the use of theoretical sciences such as mathematics, and statistics in the application areas.
| 7,8 | 1,3 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Random variables, Introduction to audio processing, basic information with time and frequency domain processing, convolution-based filtering, statistical filters, wiener filter, spectrum applications, filter design, FIR filter design, Fourier transform method, pass filtering, windowing. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to audio processing: the physical properties of sound waves, application fields of sound processing, | | | Week 2 | the audio processing techniques with MATLAB, | | | Week 3 | Artificial Audio creation: basic functions, periodic functions, random functions; | | | Week 4 | Amplitude Processes: Timing of varying amplitude, intensity processing, | | | Week 5 | Amplitude Processes: amplitude equalization, windowing; | | | Week 6 | Spatial Operations: data editing, re-sampling procedures, | | | Week 7 | Spatial Operations: delaying techniques; | | | Week 8 | Mid-term exam | | | Week 9 | MIDTERM | | | Week 10 | Segmentational operations: differential characteristics, basic statistical filters; | | | Week 11 | Integrational Processes: Fourier transform, short-time Fourier transform, spectrogram | | | Week 12 | Hilbert transform, z transform; Cepstrum Analysis | | | Week 13 | Filter operations, temporal filters, | | | Week 14 | Filter operations, frequencial filter; | | | Week 15 | Estimation methods: Inverse convolution, Wiener and Kalman filters; | | | Week 16 | End-of-term exam | | | |
| 1 | Orhan KESEMEN, Csharp ile Ses İşlemeye Giriş, (Hazırlanıyor) | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Homework/Assignment/Term-paper | 03040506070810111213 | | 3 | 50 | | End-of-term exam | 16 | 11/01/2010 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 6 | 14 | 84 | | Ödev | 10 | 12 | 120 | | Dönem sonu sınavı için hazırlık | 12 | 1 | 12 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 259 |
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