Vector quantization is a lossy compression technique used in speech
and image coding. In vector quantization, a vector is selected from
a finite list of possible vectors to represent an input vector of
samples. Each input vector can be viewed as a point in an n-dimensional
space. The vector quantizer is defined by a partition of this space
into a set of non-overlapping regions. The vector is encoded by
the nearest reference vector (known as codevector) in the codebook.

Hebbian theory is a neuroscientific theory claiming that an increase in
synaptic efficacy arises from a presynaptic cell's repeated and persistent
stimulation of a postsynaptic cell.