Hyperdimensional Computing: An Introduction to Computing in Distributed Representation with High-Dimensional Random Vectors

Source: Springer Nature Link Author: Kanerva, Pentti Date: 2009

Summary

The 1990s saw the emergence of cognitive models that depend on very high dimensionality and randomness. They include Holographic Reduced Representations, S

Why it matters here

Kanerva’s paper is the standard HDC anchor for the claim that very high-dimensional random vectors can support robust computation under noise. That is the substantive reason to consider a high-dimensional NNPL core in the first place.