Software repository for estimating human dynamics
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Updated
May 27, 2024 - C++
Software repository for estimating human dynamics
DiTEC research
Precise Point Positioning (PPP) is an advanced technique for absolute positioning using Global Navigation Satellite Systems (GNSS) with a single receiver. This approach relies on precise satellite orbit and clock information to achieve centimeter-level positioning accuracy. In this project, we process 4 hours of observation data from a Javad receiv
A estimation of pi by measuring average distance from cycles of random 2D walks.
An implementation of an Unscented Kalman Filter (UKF) for parameter identification on MATLAB.
Code for "On the Semi-Blind Mutually Referenced Equalizers for MIMO Systems", APSIPA ASC, Taipei, Taiwan, Nov. 2023
A robust sensor fusion library for online localization.
BATTERY SOC ESTIMATION USING KALMAN FILTER IN MATLAB
A statistical tool to estimate the proportion of hatchery-origin spawners using maximum likelihood estimation with parentage-based taggging
Develop a machine learning model using PPG signals to non-invasively estimate blood pressure changes in anesthetized patients during surgery. Exploring the potential of PPG-based devices for continuous patient monitoring. collaborate with:
Julia toolbox for robust control.
Python code for a polyhedral set-valued observer with an application to nonlinear systems on a Lie group.
OLS regression with possibility of controlling for fixed effects and robust standard errors
From the tiger pugmarks data estimated the number of tigers using KNN clustering
Three-point estimation is a technique to estimate tasks with triangular distribution
A statistical tool to estimate the proportion of hatchery-origin spawners using generalized least squares
RadEst is a repo for atmospheric parameters estimation using Optimal Estimation (PyOptimalEstimation) and onboard radiometer observations.
This Repository contains projects from Robotics specialization- Estimation and Learning from Coursera offered by the University of Pennsylvania- Instructor: Prof. Daniel Lee
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