Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.6 |
FileSize | 135928 |
MD5 | 3195461876A68995B5657D515AC44B57 |
SHA-1 | C57F145ADF029E1CE7120DE2426954F51B08B69F |
SHA-256 | A1BEBAEE07759841F51104BFB6961F91D19493867DC463A8B0C6B764881ACF72 |
SSDEEP | 1536:OeVieR/X0McbpzOWOJ4DwBjbzv3poM4TFkbUzP8wlTyE79+/zLKKW6rtT:HVpRlcbkWY4Dwl/WMiEUzflWb |
TLSH | T125D36D0DBE0E6812C1C1B778A34D4A5C733E2254F75670F32046D3EC5A0AEA69BB7A65 |
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 | 23C7CEA8AFFFD7CF8F0F6F8987E7C30F |
PackageArch | aarch64 |
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.fc33 |
PackageVersion | 2.6 |
SHA-1 | FF1EB3AFBF29BA7F7174167B07D8889F7FEFECC1 |
SHA-256 | CADF0CAA21A9C7FC78E20709A46FB707EBEF6BB0B4FBABE3EA0399FF2F2BC14C |