Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.2 |
FileSize | 203356 |
MD5 | 04F0520DD7AB22176200EEA285441FC2 |
SHA-1 | DE72CDD065059588C25E01DCDC1C624867F76381 |
SHA-256 | 2B023F1A881188A73F36CFB424534C641CF22247310AECC69540C3DD2598A80B |
SSDEEP | 3072:XewLh7iNZD8TQ7dBxPUEikriHqhwGpiIyJDKc++jRNRR6AkReVBj:ZheNZDaQtPqKFcDY+jRNRR8RqBj |
TLSH | T1C4146C5E6AC2C783DD7221B94E57CF8B371AA3716A3498BD8F3757A2041A8D0330BE55 |
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 | 6062C51FB9B6011511419A210E22514C |
PackageArch | s390 |
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 | 12.fc23 |
PackageVersion | 2.5 |
SHA-1 | 21ED7674874B89F6299B24696A36BF2BD755E8E5 |
SHA-256 | 49C69AFD5B4B90D4551106F85D93083D1A06432AE570656641DC540BD7F88D2F |