Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.2 |
FileSize | 229944 |
MD5 | 2E461C42EF3FFB77D7E1D63AE243B3EA |
SHA-1 | D48086A07D6AE3123BE311ECCCF001AD4FC95439 |
SHA-256 | E9443B639EB6D290D0AC40528E1653E39266891FCEDF19C8FED1AC39437BE410 |
SSDEEP | 6144:QDmOsXGviqMUDCbG2RtET3XiPrkV0HUgH:imlG2R+GPrkV0 |
TLSH | T1FD244CC77B090813ECB08EF4DD5F2BF8F79CA9166868F026174AB71A54A29F0594738D |
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 | 199CCF9038AB522C3A7F7D77763932AE |
PackageArch | ppc64 |
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 | 117C2A887E82CC1D73AAE2AC51DA7058D2355F2E |
SHA-256 | 8F6BB7F0D2BE51183C80F241816265A6570C8547F00581E8F58CD188DA21E801 |