A graduate-level deep dive into the mathematical machinery behind modern DSP: you stop thinking of signals as sequences and start treating them as vectors in Hilbert spaces, which is the unifying lens for transforms, wavelets, adaptive filters, and inverse problems. Work is six problem sets that drill the linear algebra and estimation theory, plus a research paper you pick from current signal processing journals and present orally. It assumes you are comfortable with undergraduate signals, probability, and linear algebra, and it functions as the foundational toolkit for research in communications, imaging, radar, and machine learning down the line.
→ STARS müfredatı (resmi syllabus)
The purpose of homeworks is to improve your understanding and skills related to the course topics. It is essential that you learn, in detail together with all related steps and justifications, all those topics in the homeworks. Therefore, you are not allowed to pass the questions, analysis or design steps, and the programming parts of the homeworks to someone else, let them do the work for you, and use such obtained content while preparing the homework, since such an approach will severely degra
İlk dosyayı sen atarsan — not, slayt, geçmiş sınav, çözüm, cheat-sheet, ne varsa — defter ekibi öğrenci paylaşımlarından bu dersin notlarını yazar. Drive linki / PDF / ZIP, hepsi olur.
| Dönem | Course CPA | |
|---|---|---|
| 2024-2025 Spring | 3.48 | 1 sec · 27 öğr |
| 2023-2024 Spring | 3.45 | 1 sec · 13 öğr |
| 2022-2023 Spring | 3.66 | 1 sec · 9 öğr |
| 2021-2022 Spring | 3.54 | 1 sec · 6 öğr |
| 2020-2021 Spring | 3.44 | 1 sec · 13 öğr |
| 2019-2020 Fall | 3.74 | 1 sec · 5 öğr |
| 2018-2019 Spring | 2.43 | 1 sec · 7 öğr |
| 2017-2018 Spring | 3.13 | 1 sec · 8 öğr |
| 2016-2017 Fall | 3.41 | 1 sec · 15 öğr |
| 2015-2016 Fall | 2.66 | 1 sec · 8 öğr |
Aggregate course GPA — Bilkent STARS'tan public data. Hoca-bazlı per-section detayı için STARS evaluation report →. Öğrenci anket cevapları KVKK kapsamında defter'de tutulmaz.
None.