Binary Quantization Analysis of Neural Networks Weights on MNIST Dataset

Zoran H. Peric, Bojan D. Denic, Milan S. Savic, Nikola J. Vucic, Nikola B. Simic
2021 Elektronika ir Elektrotechnika  
This paper considers the design of a binary scalar quantizer of Laplacian source and its application in compressed neural networks. The quantizer performance is investigated in a wide dynamic range of data variances, and for that purpose, we derive novel closed-form expressions. Moreover, we propose two selection criteria for the variance range of interest. Binary quantizers are further implemented for compressing neural network weights and its performance is analysed for a simple
more » ... task. Good matching between theory and experiment is observed and a great possibility for implementation is indicated.
doi:10.5755/j02.eie.28881 fatcat:bl77womljnh3ph6u3v6ihp2szm