Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.6 |
FileSize | 123536 |
MD5 | 625E10CD3D79A6E089EF5C401E2798BA |
SHA-1 | D41607E7DAD72A9F93461114E98B8E15A1731C31 |
SHA-256 | 4AB6B70B35C3EE568F5B707EE073D2875B995135971B896CEDEF028EF0308B16 |
SSDEEP | 3072:z2uM0AEbw5ofiHEdqW06XQJCUpDKg/sfliDUsl5N:quvAmw5oqHELMD3sfliQsl5N |
TLSH | T144C34A87F2B35868C0D1C474A269B117B6317409653DBA3B5B80D2702E7FF192EAFB64 |
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 | 6A0B2A54CCF5EDD4FC4D32CE1E300AF1 |
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 | 3.el8 |
PackageVersion | 2.6 |
SHA-1 | B03515D6735EDE3545CE811BBCE412E2BFF87C9C |
SHA-256 | E6C2D0BE9A7730FD16611FB15F4F4EF7C3354AE35D4A50B44BD4003F988E9E08 |