StatsPAI is for empirical researchers who would normally jump between Stata, R, and Python. Its goal is to make common Stata/R econometrics and causal-inference workflows feel native in Python: load a ...
Syndrome-based neural decoding is a promising approach for soft-decision decoding of short, high-rate codes, but the field is still wide open. Performance often lags behind classical decoders like OSD ...
Abstract: Ordered statistics decoding (OSD) requires Gaussian elimination (GE) for obtaining the most reliable independent positions (MRIPs) of the received vector. However, GE has cubic time ...
Abstract: In this paper, we propose a systematic low density generator matrix (LDGM) code ensemble, which is defined by the Bernoulli process. We prove that, under maximum likelihood (ML) decoding, ...
This research work seeks to make renewable energy more reliable, cost effective, and accessible by exploring a different energy combination system to that currently applied to wind and hydro power.