Search Results for "learning"

...In addition to built-in CAD and pre/post-processing, automatic mesh generation, and multi-physics solvers, FEATool also seamlessly integrates the state-of-the-art OpenFOAM [1], SU2, and FEniCS CFD and FEA solvers. Moreover, native itegration with MATLAB and Python allows advanced simulation scripts and programmatic use cases such as in AI and machine learning [2]. [1]: https://www.featool.com/Easy-to-Use-OpenFOAM-GUI/ [2]: https://featool.com/model-showcase/2024-11-12-CFD-and-Flow-Prediction-Based-on-Deep-Learning...

...Range-Doppler (RD) algorithm, Chirp Scaling (CS) algorithm), synthetic scenes, InSAR (interferometric) simulation including multiple terrain types (flat, conical), and polarization calibration techniques (Whitt, PARC, Quegan, Ainsworth). The readme states that these were research/learning codes, with experiments and reports, and no further maintenance is expected. InSAR (interferometric SAR) simulation and processing. PolSAR (polarimetric SAR) calibration algorithms.

...The simulation code base consists of simulated versions of most of the SPHERES core flight code and additional code that simulates dynamics, communications, and other environmental interaction. The simulation is particularly valuable during the early stages of algorithm development and implementation as an aid in accelerating the learning curve for any Guest Scientist for SPHERES. Algorithms may be implemented in C or Embedded MATLAB and executed in the MATLAB simulation environment to verify general desired behavior. With some limitations, the code used in the simulation can be directly transferred to the SPHERES hardware. We are sharing this project with the public to gather more interest for SPHERES Guest Scientists. ...

A graphical MatLab framework for estimating the parameters of, modeling and simulating static and dynamic linear and polynomial systems in the errors-in-variables context with the intent of comparing various estimation strategies.

A simulator for learning techniques for dynamic bayesian networks.