Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.6 |
FileSize | 101952 |
MD5 | E3DAEB8192F686B87CE35EF43424128A |
SHA-1 | 70F0CFFE6AEEF16086FB4F0348442FC8D75F632F |
SHA-256 | B5FED9CCBD68FB4D75584440CBEF2209D4891116D6C4307D8ACDDEDD2DA1B1ED |
SSDEEP | 1536:3Cy0Sjm9FBLpV7l2Ycg6vES6fSejgB1kZUc1Z3mnaDOt:xkFB77t6vESoUc1ZUZ |
TLSH | T183A32A8ABC419FA1C8C0A2B5937D879833131BB1E3A772479415E7346B9A52D0F3BF49 |
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 | DBA9E1E2326C4BCF4E39D8559C572348 |
PackageArch | armv7hl |
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 | Fedora Project |
PackageName | levmar |
PackageRelease | 7.fc34 |
PackageVersion | 2.6 |
SHA-1 | E9AE365C4EA8629F6DDBDA21C143C2D58FA9D877 |
SHA-256 | 8F7FDDA57FABAD5B73DFF0D73FA5774C309748C84C691B44554FE59AB71D785C |