Analog and digital signals are two fundamental types of signals used in data communication, each with distinct characteristics and applications. An analog signal is continuous in nature, meaning it can take any value within a given range. It represents information using continuously varying physical quantities such as voltage, current, or frequency. Examples of analog signals include human voice over a telephone line, audio from a microphone, or video from a camera. Analog signals are highly susceptible to noise and distortion because any small variation in the signal can affect the accuracy of the transmitted information. Their strength and quality may degrade over long distances unless amplified, which can also introduce further distortion. In contrast, a digital signal is discrete in nature. It represents information using a finite set of values, typically two states: 0 and 1, known as binary code. Digital signals are used in modern computers, digital telecommunication systems, and data networks. Since the information is encoded in discrete levels, digital signals are more resistant to noise and can be regenerated without significant loss of quality, making them ideal for long-distance communication. Digital signals also allow for easier storage, encryption, compression, and error detection compared to analog signals. While analog signals can theoretically carry more nuanced information due to their continuous nature, digital signals