Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.2 |
FileSize | 248344 |
MD5 | 0BF299A8763ABCC760D0D0DB9314C377 |
SHA-1 | A64A1F7C83B2899B9E229BC73ECC940F33A26669 |
SHA-256 | 82487AE83B60717158D60436D03CE1A1AF4C0D603B808663766B215DA6E741B9 |
SSDEEP | 6144:Na9gNuOrvpaEDh0Snhw1aKqoioqFkwGWTqj1iw6:uyu0B1DhnhIzUGWTqjM |
TLSH | T1F7344C46718118FCD1E67576A2FAB41B323330195719AEF613D24B702E2AD122F93B6F |
hashlookup:parent-total | 1 |
hashlookup:trust | 55 |
The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
MD5 | C63A57F66D8012F6585F4D6D28F2E753 |
PackageArch | x86_64 |
PackageDescription | levmar is a native ANSI C implementation of the Levenberg-Marquardt optimization algorithm. Both unconstrained and constrained (under linear equations, inequality and box constraints) Levenberg-Marquardt variants are included. The LM algorithm is an iterative technique that finds a local minimum of a function that is expressed as the sum of squares of nonlinear functions. It has become a standard technique for nonlinear least-squares problems and can be thought of as a combination of steepest descent and the Gauss-Newton method. When the current solution is far from the correct on, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge. When the current solution is close to the correct solution, it becomes a Gauss-Newton method. |
PackageMaintainer | umeabot <umeabot> |
PackageName | lib64levmar2 |
PackageRelease | 2.mga7 |
PackageVersion | 2.6 |
SHA-1 | ADE0C6F0F0D8CD050CA03BFDCBDBB4A4D2BF7F16 |
SHA-256 | 1246F8F2DAE7E216186A4C511EEB4B9D7D02B9F4D852F1BB9C4CF114662AF298 |