The term "signal spectrum" refers to the distribution of frequencies present in a signal. In signal processing, a signal spectrum provides information about the frequency components contained within a given signal. It helps analyze and understand the frequency content of a signal and is often represented graphically using a plot called a frequency spectrum.
When a signal is represented in the frequency domain, it allows us to examine the strength or amplitude of each frequency component present in the signal. The spectrum provides insights into the signal's composition, including the dominant frequencies, harmonics, noise, and other characteristics. It is particularly useful for analyzing signals that vary over time, such as audio signals, electromagnetic signals, or any other form of time-varying data.
The process of obtaining a signal spectrum involves applying a mathematical transformation called a Fourier transform to convert the signal from the time domain to the frequency domain. The result of the Fourier transform is a representation of the signal's frequency content, typically displayed as a plot showing the amplitude or power of each frequency component.
Signal spectrum analysis is employed in various fields, including telecommunications, audio processing, image processing, radar systems, and many other areas where understanding the frequency characteristics of a signal is essential. It enables tasks such as filtering out unwanted frequencies, identifying specific frequency components, detecting anomalies, or extracting relevant information from the signal.