This course will deal with advanced theory and applications of digital signal processing. This course is offered for senior undergraduate students who have basic knowledge about signal and systems and probability theory. Throughout the semester, the course covers basic digital signal processing theory including sampling theory, frequency-domain analysis of the signal and systems, structure of the filters, filter design theory, discrete Fourier transform (DFT) and short-time Fourier transform (STFT) and time-frequency analysis of signals. Then, probability theory and random process will be briefly reviewed and more advanced signal processing techniques including Wiener filter, minimum mean square error (MMSE) estimation, adaptive filtering, digital filter bank, and array signal processing techniques will be discussed. In this course, the students will practice various signal processing applications using MATLAB and C Programming.