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Author

Hamza Errahmouni Barkam

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Book Open access Aug 2026

Vector-Space Projection and Unified Complex-Valued Acceleration for Scaling Matrix-Based Brain-Inspired Representations

This work proposes a flattening methodology that preserves GHRR's matrix-based encoding while executing training and inference directly in vector space, functionally equivalent to FHRR inference yet free of permutation logic.

William Youngwoo Chung, Hyunwoo Oh, Calvin Yeung et al. · 0 citations

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