High performance computational platform in Python for the spectral Galerkin method
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Updated
May 23, 2024 - Python
High performance computational platform in Python for the spectral Galerkin method
Elegant Butterworth and Chebyshev filter implemented in C, with float/double precision support. Works well on many platforms. You can also use this package in C++ and bridge to many other languages for good performance.
An IIR filter class implementation in Python
optimizer & lr scheduler & loss function collections in PyTorch
The tools for proper interactions between ApproxFun.jl and DifferentialEquations.jl for pseudospectiral partial differential equation discretizations in scientific machine learning (SciML)
Propagators for Quantum Dynamics and Optimal Control
MFM community development code
A C++ polynomials and related algorithms.
Machine learning functions written in goLang:
Basic (+chebyshev) interpolation recipes in Julia
Object detection and recognition in digital images using Chebychev indexation and Support Vector Machines
EE 338 Digital Signal Processing, IIT Bombay
Python functions for orthogonal polynomials and (real, 2D, orthonormal) spherical harmonics
Battery Optimal Layer Design (BOLD) Toolbox for optimising layer configuration of pouch cells
Solves one dimensional Schrodinger problem using several methods.
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