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tesseract++ 0.0.1
N-dimensional tensor library for embedded systems
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Solve Ax = b for symmetric positive-definite A via Cholesky decomposition. More...
#include "config.h"#include "utilities/expected.h"#include "matrix_traits.h"#include "simple_type_traits.h"#include "algorithms/decomposition/cholesky.h"#include "algorithms/solvers/triangular_solve.h"

Go to the source code of this file.
Namespaces | |
| namespace | matrix_algorithms |
Functions | |
| template<typename T , my_size_t N> | |
| Expected< FusedVector< T, N >, MatrixStatus > | matrix_algorithms::cholesky_solve (const FusedMatrix< T, N, N > &A, const FusedVector< T, N > &b) |
| Solve Ax = b for symmetric positive-definite A via Cholesky decomposition. | |
Solve Ax = b for symmetric positive-definite A via Cholesky decomposition.
Chains cholesky() → forward_substitute() → transposed back substitution to solve Ax = b without forming the inverse. Zero dynamic allocation.
Cholesky solve (Ax = b, A symmetric positive-definite):
Complexity: O(N³/3 + N²) — dominated by Cholesky for large N.
Forwards all errors from cholesky():
From forward_substitute():