Normalisation is the process of scaling a signal or a set of values so that they fit within a desired range or have a specific statistical property. It is a fundamental operation in digital signal processing, used to prepare data for analysis, improve numerical stability, or enable meaningful comparisons between different signals.

There are several common types of normalisation, each serving a different purpose.

Peak Normalisation

Peak normalisation scales a signal so that its maximum absolute value equals a target level, usually 1.0 or a specified dB level. This preserves the shape of the waveform while adjusting its overall amplitude.

For a signal $x[n]$, the peak-normalised output is:

The Bode plot is a graphical representation of a linear system's frequency response. It shows two things together: gain in decibels and phase shift in degrees. The horizontal axis uses a logarithmic scale for frequency. The vertical axes are linear – decibels for gain, degrees for phase. Bode plots are essential for understanding filters, amplifiers, and control systems.

Think of it this way – you send a sine wave into a system and slowly increase the frequency. At very low frequencies, the output matches the input perfectly. As you approach the system's limits, the output becomes quieter (gain drops) and arrives later (phase lags). The Bode plot captures this entire behavior in one picture.

The Bessel function of the first kind is a special mathematical function that appears in many areas of physics and engineering, including wave propagation, vibrations, and digital signal processing.

In digital signal processing, it is especially important because it is used in the definition of the Kaiser window, one of the most flexible window functions for spectral analysis.

The most commonly used version in DSP is the zero-order modified Bessel function:

This function does not oscillate like sine or cosine functions. Instead, it produces a smooth, symmetric curve that grows in a controlled exponential-like manner.