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lrjxaint's Projects

dqn_of_dwa_matlab icon dqn_of_dwa_matlab

learning the weight of each paras in DWA(Dynamic Window Approach) by using DQN(Deep Q-Learning)

exampleimm icon exampleimm

This is an implement on the algorithm of the interacting multiple model algorithm.

filterpy icon filterpy

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.

firstcontactwithtensorflow icon firstcontactwithtensorflow

This repository contains the information required by the TensorFlow Hands-on at Summer Seminar ETSETB TelecomBCN, 4-8 July 2016

fucking-algorithm icon fucking-algorithm

手把手撕LeetCode题目,扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.

gaft icon gaft

A Genetic Algorithm Framework in Python

gan-keras icon gan-keras

里面包含许多GAN算法的Keras源码,可以用于训练自己的模型。

geatpy icon geatpy

A high-performance GEA framework for Python. Welcome to star and fork.

hb-cb-design-ordering icon hb-cb-design-ordering

[ICNC 2020] Hybrid Beamformer Codebook Design and Ordering for Compressive mmWave Channel Estimation

hybrid-relay-ris icon hybrid-relay-ris

Hi all, some readers ask me the code for channel modeling and Algorithms in the paper "Hybrid Relay-Reflecting Intelligent Surface-Assisted Wireless Communication" (available on https://arxiv.org/pdf/2103.03900.pdf ). I upload them here, and hope this helps!!!

idp icon idp

containing works for my IDP on Social LSTM

image_class icon image_class

基于keras集成多种图像分类模型: VGG16、VGG19、InceptionV3、Xception、MobileNet、AlexNet、LeNet、ZF_Net、ResNet18、ResNet34、ResNet50、ResNet_101、ResNet_152、DenseNet

imm_enkf_traffic_estimation_incident_detection icon imm_enkf_traffic_estimation_incident_detection

This repository contains supporting codes for the paper “Interactive multiple model ensemble Kalman filter for traffic estimation and incident detection.”. Please see readme for more details on how to run the codes.

introrl icon introrl

Intro to Reinforcement Learning (强化学习纲要)

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