A Rust library for hyperdimensional computing (HDC).

Hyperdimensional computing is a brain-inspired paradigm where information is represented as high-dimensional vectors (hypervectors or HDVs) and processed using simple algebraic operations like addition, multiplication, and permutation. This enables fast, robust, and noise-tolerant learning for tasks like classification, symbolic reasoning, and associative memory [4].

• Binary (0/1) and bipolar (+1/-1) hypervector types (HDVs).
• Real and complex hypervector types (also known as HRRs or Holographic Reduced Representations).
• Trait-based design for extensibility
• Example applications: concept inference, text image classification

1. "What We Mean When We Say 'What’s the Dollar of Mexico?'" – Pentti Kanerva, 2010
2. "Language Geometry using Random Indexing" Aditya Joshi1, Johan T. Halseth, and Pentti Kanerva, 2016
3. "A Robust and Energy-Efficient Classifier Using Brain-Inspired Hyperdimensional Computing" Abbas Rahimi, Pentti Kanerva, Jan M. Rabaey, 2016
4. "Hyperdimensional Computing: An Algebra for Computing with Vectors", Pentti Kanerva, 2022
5. "Holographic Reduced Representations", Tony Plate, IEEE Transactions on Neural Networks, February, 1995, 6(3):623-41

Three examples of problems that can be solved with hypervectors:

• Kanerva's Mexican Dollar [1] inferencing example - run it with:

  % cargo run --release --bin main_mexican
  

• Plate's inferencing example used in his HRR paper [5].
• Text language identification on a 22 language corpus [2].
• MNIST image classification - note this example is in its own repo.