CUDA C implementation of Principal Component Analysis (PCA) through Singular Value Decomposition (SVD) using a highly parallelisable version of the Jacobi eigenvalue algorithm.
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Updated
May 10, 2019 - Cuda
CUDA C implementation of Principal Component Analysis (PCA) through Singular Value Decomposition (SVD) using a highly parallelisable version of the Jacobi eigenvalue algorithm.
A way to compute PCA through CUDA and GPU
This repository is about finding the eigenvalues and eigenvectors of an image or any input matrix
Implementation of One Sided Jacobi SVD using CUDA on Jetson TK1 embedded GPU
Jacobi eigenvalue algorithm openmp implementation. Symmetric eigenvalue problem.
Vectorization of the Jacobi-type methods for the SVD and the EVD
MAL114 - Linear Algebra MATLAB Codes: QR decomposition and eigenvalues, Gauss-Jacobi, Gauss-Jordan, Gauss-Seidel, Graham-Schmidt, Jacobi Eigenvalues, Projection, Successive over Relaxation, System of Equations.
Methods for calculating eigenvalues (Holder, Jacobi, ...), optimizing functions (GD, ...)
Implementation of serial and parallel(MPI) Jacobi algorithm for estimating of eigenvalues of symmetric matrix
Matrix class + Gaussian Elimination, Jacobi Eigenvalue Algorithm, Linear Regression
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