This is Part II of the two-part comprehensive survey devoted to a computing framework most
commonly known under the names Hyperdimensional Computing and Vector Symbolic …

Hyperdimensional (HD) computing is built upon its unique data type referred to as
hypervectors. The dimension of these hypervectors is typically in the range of tens of …

We propose a unified machine learning (ML) framework for simultaneously performing
electrical load forecasting and unsupervised anomaly detection in real time. For load …

Hyperdimensional (HD) computing is a set of neurally inspired methods for obtaining
highdimensional, low-precision, distributed representations of data. These representations …

Hyperdimensional computing (HDC) is an emerging computing paradigm that imitates the
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …

Brain-inspired architectures are gaining increased attention, especially for edge devices to
perform cognitive tasks utilizing its limited energy budget and computing resources …

Thanks to the tiny storage and efficient execution, hyperdimensional Computing (HDC) is
emerging as a lightweight learning framework on resource-constrained hardware …

Hyperdimensional computing (HDC) has emerged as an alternative lightweight learning
solution to deep neural networks. A key characteristic of HDC is the great extent of …

Hyperdimensional computing (HD) is a new brain-inspired algorithm that mimics the human
brain for cognitive tasks. Despite its inherent potential, the practical efficiency of HD is tied to …

Brain-inspired Hyperdimensional Computing (HDC) is an emerging framework in low-
energy designs for solving classification tasks at the edge. Unlike mainstream neural …