Abstract: In recent years, numerous designs have used systolic arrays to accelerate convolutional neural network (CNN) inference. In this work, we demonstrate that we can further speed up CNN ...

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

Abstract: To address the degradation in radiation performance caused by external deformations in variable-curvature cylindrical conformal antenna arrays, this letter proposes a real-time beam pattern ...

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python US watchdog ...

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

TL;DR: Sony and AMD's Project Amethyst introduces Neural Arrays, Radiance Cores, and Universal Compression to enhance next-gen PlayStation consoles like the PS6. These technologies optimize GPU ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...

ABSTRACT: With the advent of the 5G and future 6G, base stations will be used as station controllers. The antenna systems are networked and equipped with a processor to optimize the detection of ...

The earthquake simulation shaking table array is an important experimental equipment with a wide range of applications in the field of earthquake engineering. To efficiently address the complex ...