One-dimensional signal spectrum usually refers to a sequence (but not limited to a digital sequence), which represents the characteristics of a signal in frequency domain. Spectrum is a mathematical tool to convert time-domain signals into frequency-domain signals, which can be used to identify the frequency components and amplitude of signals, so that we can have a deeper understanding of the characteristics of signals. One-dimensional signal spectrum is widely used in communication, electronics, acoustics, astronomy and other fields.

The significance of one-dimensional signal spectrum lies in that it reveals the characteristics of signals in frequency domain and is the basis for understanding signals. Through the analysis of frequency domain signals, we can truly understand the internal structure of signals, and then design and apply signals. Especially in the fields of audio, video and communication, spectrum analysis is an indispensable tool.

The most common method to analyze the spectrum of one-dimensional signal is to transform the signal from time domain to frequency domain through Fourier transform. Fourier transform is a method to decompose a signal into several simple frequency components, which explains the frequency structure of the signal and can be used to calculate the energy distribution and amplitude spectrum of the signal in frequency domain. Through Fourier transform, we can analyze the frequency components of signals, so as to filter and reduce noise. It is widely used in signal compression, coding and decoding.