Hardware-Efficient Compression of Neural Multi-Unit Activity Using Machine Learning Selected Static Huffman Encoders - Data and Results (2022)
Attributed to:
Functional Oxide Reconfigurable Technologies (FORTE): A Programme Grant
funded by
EPSRC
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.5281/zenodo.6265022
Publication URI: https://zenodo.org/record/6265022
Type: Journal Article/Review