Investigating the Optimal Neural Network Parameters for Decoding

2022/04/20 by Joshua Tshifhiwa Maumela, Maumela, Joshua Tshifhiwa
Computer Science · #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Neural Networks and Applications

paper · pdf · doi:10.48550/arxiv.2204.12441

openalex publication_date 2022/04/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Related

• Performance Evaluation of Channel Decoding With Deep Neural Networks
• On the Optimality of Single-label and Multi-label Neural Network Decoders
• Neural Decoding with Optimization of Node Activations
• MIND: Maximum Mutual Information Based Neural Decoder
• Achieving Low Complexity Neural Decoders via Iterative Pruning