Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.2 |
FileSize | 224616 |
MD5 | 5F1FFD5E73D503DB908C85BAC84DBFEB |
SHA-1 | 06FD26C858BAD3A369EDD9C0CAF7B729C5714B52 |
SHA-256 | 4BFB9EB39A1B2CF77714B5E16EE942A05B96359383E0C342D9FC14AE2EF7E767 |
SSDEEP | 3072:AxdPDcZ9KC05vJCw4SpqSr9Nq887dgKPI9PPV7CPVLHMngNXH0vO6NXHpbwl4kAA:AxdYcr6Sr6TdgKPAPoPlMgFHSEl4kJC |
TLSH | T1DC242B06F1A358ACC199F530A6F7B567F2323048531DB8E613C6A77029AEE115EC7B1B |
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 | 4631EF1EC0BD572F33AB8504CF118262 |
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 | Fedora Project |
PackageName | levmar |
PackageRelease | 6.el6 |
PackageVersion | 2.5 |
SHA-1 | 1D41B99BDE01020AAF2FAA945789444EB1F3099E |
SHA-256 | B697D9372AF0C04B8A8C73029A16204D093F2C56AC58482F12C775C60DF615B2 |