Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.2 |
FileSize | 250056 |
MD5 | E0787E474B94177D2ECFDDAEC56AD9F1 |
SHA-1 | 2CCFD308C1A25A2C957089F3BE9E84051B95EC36 |
SHA-256 | C109E58054DD2796E3E1310342D8877321082CDD957A4B0C647E4D28A4C96720 |
SSDEEP | 6144:9XvWfgXIpIEzxPLMKvGppo3p+3UKblA99UcTfx4y2:9/WfgX43zxPLMKvepo3oBbl+9hfx4y2 |
TLSH | T16D343C47704228FCD1D5B571A2FAB12B7232301A5B1E6DE213D24B702F29D152F96B6F |
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 | 261F11224439968E930D7FFC6488F787 |
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 | 3.mga8 |
PackageVersion | 2.6 |
SHA-1 | A497D602A5059374C4C1C9CA607DF9B34F7D0B6D |
SHA-256 | 408E2E30A30F3F9632903D6C05DA521F9C5C4535E70EA07E56308981CCDF3551 |