Course starts with the introduction of communication systems: components of communication systems, analog and digital messages, conversion from analog to digital signal (A/D conversion). Explanation for most important terms in communications: signal-to-noise-ratio, channel bandwidth and the rate of communication. Modulation as a process of signal conversion for the purpose of appropriate transmission. We will also introduce concepts of randomness, redundancy and coding, which represent the basis of communications.
Further, course describes the basic signal concepts: size of the signal, classification of signals as well as some useful signal operations. We will cover the topics such as analogy between signals and vectors, comparison between signals, and finally, correlation that measures the degree of similarity (agreement or alignment) of two signals. Signal representation by orthogonal signal set: orthogonal vector space, orthogonal signal space. We will describe spectral representation of periodic signals: trigonometric Fourier series, exponential Fourier series. Also, spectral representation of aperiodic signals will be emphasized such as Fourier integral, properties of Fourier transform, and so on. At the end of the semester we will work on signal transmission through a linear system, ideal and practical filters, signal distortion over a communication channel, signal energy (power) and energy (power) spectral density.  At the end numerical computation of Fourier transform, DFT will be briefly covered.