Investigating the Optimal Neural Network Parameters for Decoding
arXiv:2204.12441v1h-index: 1
Originality Synthesis-oriented
AI Analysis
Incremental improvement for telecommunications decoding efficiency.
This thesis investigates optimal neural network parameters to improve efficiency in decoding for telecommunications, focusing on minimizing inversion errors.
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.