Spektrogramet

Spektrogramet is a visual representation of the spectrum of frequencies of a signal as it varies with time. It is commonly used to analyze sound signals, but can also be applied to other types of signals such as seismic waves or radar.

A spectrogram is typically generated by performing a Short-Time Fourier Transform (STFT) on the signal. The STFT divides the signal into small overlapping segments, and then computes the Fourier Transform for each segment. This process reveals the frequency content of the signal over short time intervals.

The resulting spectrogram is a two-dimensional plot where the horizontal axis represents time, the vertical axis represents frequency, and the intensity or color at each point indicates the amplitude of that frequency at that specific time. Low frequencies are usually displayed at the bottom of the plot, and high frequencies at the top.

By examining a spectrogram, one can identify patterns and characteristics of a signal that might not be apparent in a time-domain representation. For example, in audio analysis, spectrograms can reveal the fundamental frequency of speech, the presence of harmonics, and the temporal evolution of different sounds. This makes them a valuable tool in fields such as speech recognition, music analysis, bioacoustics, and signal processing. The resolution of a spectrogram in time and frequency is inherently linked through the Heisenberg uncertainty principle, meaning that improving resolution in one domain comes at the expense of the other.