Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.2 |
FileSize | 208992 |
MD5 | 07E22334D58C0248DE3D7A180706C827 |
SHA-1 | 6FD38C169BE3A6AAF0E7DFD3B57E2F4B38C1BEC1 |
SHA-256 | 6274ADE2EA1F3412DD2D802AA81DC571E7F744781D989D59434AB2153CC73C04 |
SSDEEP | 6144:vogZANNrBUU6T7g5xa4Vr5yW7TW+5DpTHO:CrL6AZPx0 |
TLSH | T1E3149E1AE60EFE6AC0C1F7B1DD5E4D4C7309248A8323719EE600C3F67696AB466F4B15 |
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 | FF5FC1FC185619BA42D2380B830E0F04 |
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 | umeabot <umeabot> |
PackageName | lib64levmar2 |
PackageRelease | 3.mga8 |
PackageVersion | 2.6 |
SHA-1 | 941BD2ECCBAED0ACE4FBC99B24E3919C00609CF2 |
SHA-256 | 7C38653C140A64DFF41E1DD38AB209E5CC891152456067375F9B76505A3B3113 |