Meta-analysis toolbox for basic research applications. Developed in MATLAB R2016b.
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Updated
Apr 21, 2019 - MATLAB
Meta-analysis toolbox for basic research applications. Developed in MATLAB R2016b.
Implementation of the algorithm described in the following paper. Korenberg, M., Billings, S.A. and Liu, Y.P. (1987) An Orthogonal Parameter Estimation Algorithm for Nonlinear Stochastic Systems
Elegant Mathematica-style model manipulation, fitting and exploration in MATLAB.
Semester Project for Timeseries Course / Aristotle University of Thessaloniki / Winter Semester 2020
GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga
This MATLAB script fits either a linear or hyperbolic function to time-series data (e.g., growth data).
code to infer model parameters from data (first dedicated to the dynamic clicks task)
The project involves projective geometry, geometric transformations, modelling of cameras, feature extraction, stereo vision, recognition and deep learning, 3d-modelling, geometry of surfaces and their silhouettes, tracking, and visualisation.
Files used for the Cibernetica Fisiologica project. I've used the Matlab sensitivity toolbox to find the parameters that make the model fits the data simulated.
Reference repository for code used in our NBDT publication on the dynamic clicks task
a gradient-based optimisation routine for highly parameterised non-linear dynamical models
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