There are 0 repository under linearization topic.
This code studies a linearized PF model through a data-driven approach.
Controllers designed to the 5MW NREL wind turbine using Simulink and Fast V8
Interface between ControlSystems and ModelingToolkit
A package for doing Solidity and Python-style C3-linearization in ECMAScript
Cooperative multiple inheritance for CoffeeScript, à-la Python. http://sinusoid.es/heterarchy/
Files related to my Summer of Science Report on Nonlinear Dynamics
Zero + is a Gomoku AI that implements threat space search, minimax with alpha beta pruning optimized with Zobrist and linear sequence cache, Principal Variation Search, and Monte Carlo Tree Search.
Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event
Strongly consistent distributed key-value store
Repository for AUV Control Optimisation using LQR Project with ECA Group
Feedback linearization for quadrotors
Functions and guide to use automatic differentiation for material modelling in deal.II on the element and QP level
Adaptive linearization of bezier curves / SVG paths
This is a library with different sub-libraries to provide basic functions, which can be used in data and signal processing and to compare measurement results against simulation.
Repository to design and implement LQR control on an AUV by ECA-Group
A/B testing statistics, design, increasing sensitivity, multiple experiments comparison, traffic splitting and full A/B testing pipeline in Python
Search for linearizing sets to solve inversion problem
Interpreting neural networks by reducing nonlinearities during training
Fault Tolerance Project
a quadratic linealization example, using python-mip library and coinOR solver
A website I created giving a brief overview of mathematical optimization techniques. These techniques can be useful in understanding the intuition behind machine learning algorithms.
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.