byf666
Follow
Starred repositories
This repository contains data and codes that support the plots and RC simulations within the paper.
Optical transmition of an Direct Detection system using FFE and ESN reservoir for equalization of dispersion
Reservoir Computing using Optical Processing Units of LightOn
This repository implement a reservoir computer using Matlab simulation. It harness the nonlinearity property of optical fiber in achieving a reservoir. Optical fiber is used to serve as the nonline…
Neural network (reservoir computing system) based on electro-optical delay setup
python library to design chips (Photonics, Analog, Quantum, MEMs, ...), objects for 3D printing or PCBs.
Main public repository for the Scalable Photonic Event-driven Circuit Simulator.
pytorch 实现在MNIST数据集上训练FC和CNN，并将训练好的模型在自己的手写图片数据集上测试
基于Pytorch的卷积神经网络MNIST手写数字识别 适用于Pytorch与神经网络入门学习
This is a framework for binary neural network based mmclassification
An Example of CNN on MNIST dataset
Perform tasks with binary convolutional neural networks!
DOCTOR (Dynamic on-chip calibration for self-corrected photonic tensor cores), IEEE JLT 2024
A PyTorch Library for Photonic Integrated Circuit Simulation and Photonic AI Computing
Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
A matlab coding framework and component library for simulation and experimental analysis of optical communication systems
Simulate optical communications systems with Python.
hybrid optical electronic convolutional neural networks
A tool for mapping and simulating convolutions using ultrafast photonics
Feature-based Knowledge Distillation combining geometric perspective for local activations and H. Barlow’s principle for global response.
randomized QB factorization for fixed-precision low-rank matrix approximation
randQB_EI (i.e. svdsketch in MATLAB) algorithm and others
Applied k-means clustering to quantize a color space and implemented Hough transform to detect circles of chosen radius.
Color Reduction and Quantization using k-Means Clustering
This project presents the feature extraction techniques so-called Quantization-based Position Weight Matrix (QuPWM) methods for biomedical classification.
Optimization and Acceleration of Real-Time Deep Learning Neural Networks for Time-of-Flight Imager Data Classification: Quantization, PCA-based Feature Extraction, and Network Pruning
Some proof of concept methods of quantizing the weights of neural networks
