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reinforcement_learning_for_stock_prediction

This is the code for "Reinforcement Learning for Stock Prediction" By Siraj Raval on Youtube

reinforcement_learning_team_q_learnig_marl_multi_agent_uav_spectrum_task

A solution for Dynamic Spectrum Management in Mission-Critical UAV Networks using Team Q learning as a Multi-Agent Reinforcement Learning Approach

reinforcement_learning_tutorial_with_demo

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

relaxation-algorithm-on-ris-miso

Transforming RIS-Assidted Passive Beamforming from Tedious to Simple: A Relaxation Algorithm for Ricain Channel

relaxed-grpda

golden ratio primal-dual algorithm with relaxed parameters

reliability-analysis-of-autonomous-uav-communication-using-statistical-model-checking

This Git repositry includes the xml file used in the Reliability Analysis Of Autonomous UAV Communication Using Statistical Model Checking paper. To open the file please use the uppaal-4.1.20-stratego-7 tool. The file include the templates for all the models used in our framework.

remo

Repeated MCIK-OFDM with enhanced transmit diversity under CSI uncertainty (Index Modulation)

research-paper

:tokyo_tower: Optimisation clustering approach for energy efficiency in wireless network

research-paper---comparison-of-cnn-and-contour-algorithm-for-number-identification-using-hand-gestur

There are many applications where hand gesture can be used for interaction with systems like videogames, controlling UAV’s, medical equipment’s, etc. These hand gestures can also be used by handicapped people to interact with the systems. The main focus of this work is to create a vision based system to identify sign language gestures from real-time image capturing. The reason for choosing a system based on vision relates to the fact that it provides a simpler and more intuitive way of communication between a human and a computer. Our project has developed 3 modules that involve 49 different gestures overall, which can be predicted.

reshaped-wirtinger-flow

reshaped Wirtinger flow and Incremental reshaped Wirtinger flow for solving quadratic systems of equations

resilient_rrm_gnn

Implementation code for the paper "Learning Resilient Radio Resource Management Policies with Graph Neural Networks" submitted to IEEE Transactions on Signal Processing.

resource-allocation-using-deeprl

Deep Reinforcement Learning Based Dynamic Resource Allocation in 5G Ultra-Dense Networks

resource-allocation-using-min-max-algorithm-adverserial-search

Allocated resources to two contentious organisations based on a set of factors by mutating the Min-Max algorithm to maximise the utility value of the respective organisations

resourceallocation

resourceallocationdelayedcsi

This project contains MATLAB codes for the paper: L. Liang, J. JoonBeom, S. C. Jha, K. Sivanesan, and G. Y. Li, “Spectrum and power allocation for vehicular communications with delayed CSI feedback,” IEEE Wireless Communications Letters, vol. 6, no. 4, pp. 458–461, Aug. 2017.

resourceallocationreinforcementlearning

intial version

resourceallocationv2xgraph

This project contains MATLAB codes for the paper: L. Liang, S. Xie, G. Y. Li, Z. Ding, and X. Yu, “Graph-based resource sharing in vehicular communication,” IEEE Transactions on Wireless Communications, vol. 17, no. 7, pp. 4579–4592, Jul. 2018.

resume-website

inst630

review-response-template

LaTeX template for the response to reviewer comments (scientific journal publications)

rf-based-drone-surveillance-with-dl

rf-cmoco

Handing Wang, Yaochu Jin, A Random Forest-Assisted Evolutionary Algorithm %for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems IEEE Transactions on Cybernetics, accept, 2018.

rf-ddpg

rfl21-elm

Random Fourier Extreme Learning Machine with l2,1 -Norm Regularization

rice-crop-insects-and-weed-detection-using-faster-r-cnn

As the increase in the world population the demand of the rice is also increases. In order to increase the growth of rice in the rice crop it is necessary to detect the weed and insects in the rice crop to minimize the growth of weed and insects so that the growth of the rice can be increased.Insect and Weed detection is the important factor to be analyzed. Unmanned Air Vehicle (UAV) is used for data acquisition of rice crop in different phases and states so that high quality of RGB images can be captured. In which we have taken 15 different types of rice crop insects species images and different phases of weed images to train the model. The proposed method facilitates the extraction of weed and insects into the rice crop field using deep learning concept faster region-based convolutional neural networks(Faster R-CNNs) it is implemented using Python3 with the help of Tensorflow API. The result shows that Faster R-CNN method is the state of arts method for detection and classification of weed and insects with good accuracy rate.

rician-massive-mimo

Simulation code for “Massive MIMO with Spatially Correlated Rician Fading Channels,” by Özgecan Özdogan, Emil Björnson, and Erik G. Larsson, IEEE Transactions on Communications, To appear

riemannian-subgradient-methods

This package implements Riemannian subgradient methods for solving nonsmooth optimization problems over Stiefel manifold

ris-aided-fual-functional-radar-and-communications-beamforming-design

Beamforming optimization for a dual-functional radar and communication system, wherein a reconfigurable intelligent surface is deployed to enhance the performance.

ris-communucation-systems-code

all the self-implement of the RIS related papers

ris-distance-dependent-rician-channels

Simulation code for “RIS-Assisted High-Speed Communications with Time-Varying Distance-Dependent Rician Channels,” by K. Wang, CT. Lam, and BK. Ng, Applied Sciences, 12, no.22: 11857, 2022.

ris-in-vehicular-networks-via-drl

Deep Reinforcement Learning and BCD to solve phase shift and resource allocation of RIS and RSU