Investigating the Optimal Neural Network Parameters for Decoding

TL;DR

This paper explores how to optimize neural network parameters to improve decoding efficiency in telecommunications, focusing on minimizing inversion errors.

Contribution

It investigates the impact of various neural network parameters on decoding performance, providing insights into optimizing neural decoders.

Findings

Identification of key parameters affecting decoding accuracy

Analysis of parameter effects on inversion error rates

Recommendations for neural network configuration in decoding tasks

Abstract

Neural Networks have been proved to work as decoders in telecommunications, so the ways of making it efficient will be investigated in this thesis. The different parameters to maximize the Neural Network Decoder's efficiency will be investigated. The parameters will be tested for inversion errors only.