SAMPLING
The Sampling Theorem: A Fundamental Concept in Signal Processing The sampling theorem, also known as the Nyquist-Shannon sampling theorem, is a fundamental concept in signal processing that describes the conditions under which a continuous-time signal can be sampled and reconstructed without loss of information. In this blog, we will delve into the details of the sampling theorem, its importance, and its applications. What is the Sampling Theorem? The sampling theorem states that a continuous-time signal can be reconstructed from its samples if the sampling rate is greater than twice the highest frequency component of the signal. Mathematically, this can be expressed as: fs > 2B where fs is the sampling rate and B is the bandwidth of the signal. Importance of the Sampling Theorem : The sampling theorem is crucial in signal processing because it allows us to convert continuous-time signals into discrete-time signals, which can be processed and anal...