NozllNo

NozllNo's Stars

• hihopey/Clouds

  Uses Mie scattering to plot Attenuation vs. Frequency for different cloud types

  Language:Matlab11

• refetaliyalcin/monte-carlo-mie-scattering-in-sphere

  Language:MATLAB1

• WHLiao/Mie-Scattering-Simulator

  Wrote by MATLAB

  Language:Matlab11

• ayusmin/Mie-Scattering

  MATLAB codes to calculate the scattering, absorption and extinction coefficients of pristine as well as coated spheres using the resonance conditions for Mie Scattering.

  Language:MATLAB1

• refetaliyalcin/monte-carlo-mie-scattering

  to find the scattering angle, this code uses scattering phase function not the Henyey Greenstein function

  Language:MATLAB5

• andrea-baldi/Mie_Scattering_and_Absorption_Sphere

  Calculate scattering, absorption, and extinction cross-sections of a spherical particle

  Language:MATLAB11

• smite/mie

  Mie scattering package for MATLAB

  Language:Matlab42

• Trankwery/MR_Fin

  Solving invers problem for Mie scattering

  Language:Matlab24

• refetaliyalcin/monte-carlo-mie-scattering-polydisperse-particles

  monte-carlo-mie-scattering-polydisperse-particles

  Language:MATLAB103

• dglennie/mc_tissue_sphere_mega

  Monte Carlo simulation for measuring photons detected with sphere over tissue used to calculate scattering losses as a function of optical properties

  Language:Matlab21

• JoulesCESAR/Photon-scattering

  A litle project on photon scattering

  Language:MATLAB2

• cs7org/neuralVNC17

  Christina Stadler, Xenia Flamm, Thomas Gruber, Anatoli Djanatliev, Reinhard German and David Eckhoff, "A Stochastic V2V LOS/NLOS Model Using Neural Networks for Hardware-In-The-Loop Testing," Proceedings of 9th IEEE Vehicular Networking Conference (VNC 2017), Torino, Italy, November 2017

  Language:Matlab21

• jesuspapgga/Cooperative-energy-spectrum-sensing

  Centralized cooperative spectrum sensing with soft fusion of energy measurements in highly mobile environments. Neyman-Pearson (NP) detection criterion. Three methods: LRT (assuming the instantaneous SNRs at the cognitive radios are known by the fusion center, Generalized LRT (GLRT), Online Expectation-Maximization (EM) based algorithm that jointly estimates the SNRs and detects the presence of primary signals.

  Language:MATLAB173

• ChoeHyeongSoo/UWB-NLoS-LoS-Classification-for-KF

  Research of UWB NLoS/LoS Classification Using ML

  Language:Python4

• johnbodhi/np-detector

  Neyman-Pearson Detector

  Language:MATLAB2

• serrHendrik/nlos_classifier

  Language:MATLAB63

• SambitSatapathy9/Clustering_Algorithms

  This repository consists of the scripts and plots for the estimation of a background in mono-photon final state using the 2017 datasets collected by the CMS Detector at the LHC.

  Language:C1

• NattyBumppo/background_subtraction_paper

  A repository to organize development of a paper, along with demonstration code, for investigating different background subtraction methods.

  Language:Matlab22

• YueCui-Labs/FFCM-MRF

  MATLAB GUIs for ToF-MRA data preprocessing, cerebrovascular segmentation and quantification

  Language:MATLAB122

• gkh178/noise-adaptive-switching-non-local-means

  Aiming at the removal of salt-and-pepper noise, a noise adaptive switching non-local means denoising algorithm (NASNLM) is proposed in this program. For noise detection, the pixels of image are divided into the noise and the non-noise points. For filtering, four different filtering techniques are adopted: switching filtering, noise adaptive median filtering, edge-perserving filtering and non-local means filtering. Switching filtering can keep the gray-value of non-noise points unchanged. Noise adaptive median filtering can suppress the high-density salt-and-pepper noise. Edge-preserving filtering can preserve more image edges and details. Non-local means filtering can further improve the ability of noise suppression and detail maintenance. Experiments demonstrate that for removal of the high-density salt-and-pepper noise by NASNLM algorithm, a better denoising effect is obtained than other methods.

  Language:Matlab3718

• XinjianOUYANG/Quantum_Physics

  量子物理、量子计算相关资料

  Language:C++6811

• fengxiaohua102/Single-photon-single-pixel-imaging

  Contains the code and experimental data for the paper "Single photon single pixel imaging into thick scattering medium"

  Language:MATLAB51

• Seattlice/CFAR-Target-Detection-Processing-Simulation-Experiment---matlab

  In order to objectively evaluate the performance of various CFAR detectors, clutter is classified into three typical cases as follows: (1) uniform background clutter (2) Clutter edges (3) Multi-interference target clutter.he simulation experiment discusses the classification of these three types of cases, obtains the results .

  Language:MATLAB6

• Santoshkasam/RADAR-target-generation-and-detection

  In this project, an FMCW RADAR is configured. The transmite and recieved are processed uisng FFT and CFAR to determine the range and velocity of the obstacle"

  Language:MATLAB4

• DingdongD/CFAR_Lib

  This repository is dedicated to the simulation research of constant false alarm rate (CFAR) detection algorithms for millimeter-wave radar. It encompasses various algorithms, including but not limited to mean, ordered statistics, truncated mean, automatic selection, etc.

  Language:MATLAB84

• flappyimi/Radar-Basic-Algorithm

  Some basic algorithm used in Radar data process, including pulse compression/CFAR/monopulse、Kalman filter and fusion、arrary antenna design.

  Language:MATLAB14846

• Dingyi-Ji/BM4D_denoise_NLOS_data

  利用BM4D算法对于共聚焦非视域成像所获得的数据进行去噪处理

  Language:MATLAB2

• zhuchenqd/machlearnlocalize

  Project that aims to determine agent positions by identifying and mitigating NLOS signals. The ranged distances are then processed by a localization algorithm.

  Language:Matlab61

• xukaiyuan/NLOS-data-detection

  Data communication under None-Line-Of-Sight wireless communication scenario

  Language:Matlab51

• blinkwalk/Passive-IoT-Localization-Technology-Based-on-SD-PDOA-in-NLOS-and-Multi-path-Environments

  Reference source code for the paper “Passive IoT Localization Technology Based on SD-PDOA in NLOS and Multi-path Environments”

  Language:MATLAB3