This course covers the basic and fundamental digital signal processing techniques and it’s applications in time and frequency domain. Analog-to-digital signal conversion, symbolization of digital signal. Sampling and Reconstruction of continuous time signals, Characterization and properties of discrete time signals and systems, Computation of discrete time Fourier transform and its properties. Especially the relationship between time domain and frequency domain. The purpose of this course is to provide a common background for subsequent course work in the study of Digital signal processing and it’s applications. The contents of this course include digital signal filtering, analysis of Fast Fourier transform and, FIR/IIR filter design techniques, overlap-add, overlap save techniques and windowing methods. Project : Basic coding techniques about the lectured theory are dealt through computer programming by using Matlab. Implementation of structures for discrete time systems, Digital filter, overlap-add/save systems, window, voice active detection.