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a-deep-learning-based-spectrum-occupancy-prediction-model-for-opportunistic-access

c-

cs-base

图解计算机网络、操作系统、计算机组成、数据库，共 1000 张图 + 50 万字，破除晦涩难懂的计算机基础知识，让天下没有难懂的八股文！🚀 在线阅读：https://xiaolincoding.com

deep-reinforcement-learning-for-dynamic-spectrum-access

Using multi-agent Deep Q Learning with LSTM cells (DRQN) to train multiple users in cognitive radio to learn to share scarce resource (channels) equally without communication

drcf

Rainfall forecasting is a very important problem in the field of hydrology and meteorology. Especially, short-term rainfall forecasting is closely related to resident's daily life. For example, forecasting the situation of stagnant water on the road, providing weather guidance for the flight, and providing short-term heavy rainfall warning in the city.However, existing solutions achieve low prediction accuracy for short-term rainfall forecasting. Numerical forecasting models can achieve overall accuracy but always perform worth in some short-term conditions. Data-driven approaches always neglect the influences of physical factors in upstream or downstream regions, which lead to the forecasting accuracy fluctuates in different areas. Rainfall forecasting is affected by many factors, such as high-altitude physical factors and surface factors.High-altitude physical factors play important roles in the movement of rainfall system. Surface factors on the Earth also cause different rainfall. Difference surface factors represent different factors between region and surrounding area. Therefore, it is very reasonable to forecast rainfall by studying the relations between high-altitude physical factors, surface factors and rainfall. In this project, a Dynamic Regional Combined short-term rainfall forecasting model (DRCF) using Multi-Layer Perceptron (MLP) is proposed. The input of the model includes five high-altitude factors and seven different surface factors. In summary, we have addressed a series of techniques challenges in this work, and the central contributions are summarized as follows: 1.Principle Component Analysis (PCA) is used to determined the input of of MPL and a special greedy algorithm is proposed to determine the suitable structure of MLP. 2.The relation between forecasting area and surrounding area is established using MPL. Based on the relation, a dynamic regional combined rainfall forecasting model is proposed. The strategy of dynamically adjusting area is also enhanced to effectively improve prediction accuracy. 3.The model is finally validated by a large number of meteorological site data, including 56 sites, and these sites are distributed in all parts of China.

envaluate

Upconverting nanoparticle output spectrum prediction tool.

epsilon-greedy-and-upper-confidence-bound-algorithms

frequency-hopping

A plain simulation model for Frequency Hopping

frequency-hopping-spread-spectrum-simulation-using-matlab

Frequency Hopping Spread Spectrum Simulation using Matlab

greedy-algorithms-for-hybrid-compressed-sensing

greedy-sensor-selection-algorithm

This repository contains Matlab R2020a code to solve the sparse sensor selection problem by the greedy method

greedy_cs

Collection of greedy algorithms for sparse recovery.

learn_drl

学习DRL CNN -> DQN -> LSTM

line-spectrum-pairs-interpolation

Audio Interpolation method based on Line Spectrum Pair polynomials, allowing for better results for same model order compared to ordinary linear prediction interpolation.

lstm-matlab

LSTM-MATLAB is Long Short-term Memory (LSTM) in MATLAB, which is meant to be succinct, illustrative and for research purpose only. It is accompanied with a paper for reference: Revisit Long Short-Term Memory: An Optimization Perspective, NIPS deep learning workshop, 2014.

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

lstm-prediction

LSTM Prediction for time series data (jean sales data set) using matlab

lstm-regression

use LSTM to implement regression and predict

lstmforecastsells

LSTM applied to forecast sells for 1C Company

model

The source code of LIC-LSTM model introduced in paper: Layerwise Interweaving Convolutional LSTM

modular-rl

[ICML 2020] PyTorch Code for "One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control"

motion-prediction-of-a-star

Prediction of motion of a star using MATLAB/Octave based on the its spectrum

ms2pbpi

Peptide fragment ion mass spectrum prediction by data mining methods

multiple-agent-interaction

Comparison of four Q-learning algorithms that include interaction of agents.

mwc

Matlab code for Analog to Information of Frequency Hopping signal based on Modulated Wideband Converter

open-interpreter

OpenAI's Code Interpreter in your terminal, running locally

playwright

Playwright is a framework for Web Testing and Automation. It allows testing Chromium, Firefox and WebKit with a single API.

playwright-python

Python version of the Playwright testing and automation library.

price_prediction_for_700_mhz_in_spectrum_auction

In this Project, we have done prediction of the price of 700 Mhz spectrum using 2d polynomial regression, Ridge, LinearRegression.

pylearn2

Warning: This project does not have any current developer. See bellow.