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Hardware-Efficient Compression of Neural Multi-Unit Activity Using Machine Learning Selected Static Huffman Encoders - Data and Results (2022)

First Author: Savolainen O

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