Course on Advances in Digital Signal Processing (DSP) session began by distinguishing between analog, digital, and discrete signals. Analog signals are continuous in time and amplitude, whereas digital signals are represented by discrete values. Discrete signals, however, have discrete time intervals but can have continuous amplitude. The professor then delved into quantization, explaining how continuous amplitude signals are converted into discrete level. Sampling, the process of converting continuous-time signals into discrete-time signals, was also covered. The Nyquist-Shannon sampling theorem was introduced, emphasizing the importance of sampling greater than twice the highest frequency component. Key concepts discussed included:
- Discrete time signal Vs Digital signal
- Continuous time signal & Continuous phase signal
- Sampling interval and frequency
The session provided a solid foundation for understanding the fundamental principles of DSP, paving the way for further exploration of signal processing techniques and applications. By clarifying the differences between analog, digital, and discrete signals, the professor set the stage for in-depth analysis of sampling and quantization, crucial steps in converting real-world signals into digital representations.
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