Hyperdimensional Computing Model

Hyperdimensional computing (HDC) is a lightweight machine learning approach using high-dimensional binary vectors for efficient classification and pattern recognition, particularly suited for resource-constrained devices like those in the Internet of Things. Current research focuses on optimizing HDC's efficiency and accuracy through techniques such as reduced dimensionality, binarized data encoding, and improved training algorithms that consider confidence levels. These advancements aim to enhance HDC's performance in various applications while minimizing computational and energy demands, making it a compelling alternative to more complex deep learning methods.