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"From OTFS to AFDM: A Comparative Study of Next-Generation Waveforms for ISAC in Doubly-Dispersive Channels" [https://arxiv.org/abs/2401.07700]: by Hyeon Seok Rou, Giuseppe Thadeu Freitas de Abreu,…
This repository is a fundamental toolbox of OTFS modulation crossing multiple platforms.
A curated list of resources for using LLMs to develop more competitive grant applications.
This package contains the code to run Learned D-AMP, D-AMP, D-VAMP, D-prGAMP, and DnCNN algorithms. It also includes code to train Learned D-AMP, DnCNN, and Deep Image Prior U-net using the SURE loss.
This repository presents the codes for reproducing the paper "LSTM-Based Time-Frequency Domain Channel Estimation for OTFS Modulation".
Codes for Complex-Valued Spectrum Estimation Network and Applications in Super-Resolution HRRPs Analysis with Wideband Radars
Data-driven implementaion of soft iterative interference cancellation for MIMO detection
This repo contains simulation code for DI-S-MMSE Turbo Equalizer and LMMSE Equalizer applied to OTFS Modulation.
A QPSK modem written in the Verilog hardware description language, that can be implemented on FPGA
Overview and implementation of Belief Propagation and Loopy Belief Propagation algorithms: sum-product, max-product, max-sum
Book_4_《矩阵力量》 | 鸢尾花书：从加减乘除到机器学习；上架！
Book_1_《编程不难》 | 鸢尾花书：从加减乘除到机器学习；请多多批评指正！
Reference implementation of GFDM framework
MATLAB demonstration for the paper 'Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems'
Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex-valued Convolutional Networks
Xilinx FPGA, ADC344X, AD9252, 14x 12x Serdes, LVDS
LBNL RF controls support HDL libraries. Mirroring LBNL's internal Gitlab repository, which is CI enabled
💻深度学习实战：手写数字识别、Discuz验证码识别、垃圾分类、语义分割
仅使用numpy从头开始实现神经网络,包括反向传播公式推导过程; numpy构建全连接层、卷积层、池化层、Flatten层；以及图像分类案例及精调网络案例等,持续更新中... ...
A Verilog design of LeNet-5, a Convolutional Neural Network architecture
Project is about designing a Trained Neural Network on FPGA to classify an Image Input using CNN.