GitHub

Kalman and Bayesian Filters in Python

Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Jupyter Notebook so that you can run and modify the code in your browser. What ...
GitHub

Getting started with Ollama for Python

So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...
IEEE

Adaptive Learning-Rate Backpropagation Neural Network Algorithm Based on the Minimization of Mean-Square Deviation for Impulsive Noises

Abstract: This paper presents a novel adaptive learning-rate backpropagation neural network (ALR-BPNN) algorithm based on the minimization of mean-square deviation (MSD) to implement a fast ...
IEEE

Reducing Training Time of Deep Learning Based Digital Backpropagation by Stacking

Abstract: A method for reducing the training time of a deep learning based digital backpropagation (DL-DBP) is presented. The method is based on dividing a link into smaller sections. A smaller ...