No, it is not.
discrete
The Discrete Fourier Transform (DFT) is a specific mathematical algorithm used to compute the frequency spectrum of a finite sequence of discrete samples. In contrast, the Discrete-time Fourier Transform (DTFT) represents a continuous function of frequency for a discrete-time signal, allowing for the analysis of signals in the frequency domain over an infinite range. Essentially, the DFT is a sampled version of the DTFT, applied to a finite number of samples, whereas the DTFT provides a broader, continuous frequency representation of the signal.
The two main kinds are discrete and continuous.
The analog signal is converted to discrete signal. Even after the conversion, the frequency of the actual signal still remains the same. If the frequency of the discrete signal is different from the analog signal, the reconstructed signal would be different again. This is not what we expect. So base spectrum for similar signals have same frequencies, whether they are discrete or analog. Why do the repetitions occur? The original analog signal is multiplied with a dirac pattern. The base frequency is then shifted to the places, where diracs are available. So long the diracs keep repeating, the base frequency do repeats. Hope you are convinced with my answer
discrete because the signal of an alarm is periodic.
To answer this properly more context is needed but frequency is in most contexts continuous.
The frequency domain of a voice signal is normally continuous because voice is a nonperiodic signal.
Species
FDM stnds for frequency division multiplexing and it is used only in case of analog signals because analog signals are continuous in nature and the signal have frequency. TDM-stands for time division multiplexing and it is used only in case of digital signals because digital signals are discrete in nature and are in the form of 0 and 1s. and are time dependent.
A photon is a small discrete unit of energy that is associated with light. It behaves both like a particle and a wave, carrying a specific amount of energy depending on its frequency.
In signal processing, sampling is the reduction of a continuous signal to a discrete signal. A common example is the conversion of a sound wave (a continuous signal) to a sequence of samples (a discrete-time signal).
The frequency of a guitar note can be determined by measuring the number of vibrations per second. This frequency is represented as a continuous value because it can vary smoothly across a range of pitches.