Result for DB9776448C914027143DE76BB32CCA4825DC4CAE

Query result

Key Value
FileName./usr/lib/liblevmar.so.2.6
FileSize131092
MD51554F369D77DF27B82BB66C0905F0CD8
SHA-1DB9776448C914027143DE76BB32CCA4825DC4CAE
SHA-256608520CD3F09962F09B10EE785912781F50C6279B8AE320D23801316B145750B
SSDEEP3072:WV7OLg6F4DNR/3bcqIKWnQJkKk4PmJPJR9VI3SuDhneSw+SF:WxOLgg6gKWnQJkKk4POPJjVI3SuDhw
TLSHT150D33955F782A5B0E0D310F0061B36AB222012197177F1B3F7C6BB95A87E6927E9B335
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

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
MD52430BDE44BE45B43AC80B940248E3D01
PackageArchi686
PackageDescriptionlevmar 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.
PackageMaintainerFedora Project
PackageNamelevmar
PackageRelease2.fc32
PackageVersion2.6
SHA-15F239633CD3D34671681A1408962F01B4B1826AE
SHA-25667338F65AAF1888C621BC9ADAE059D75670879196D8E9221A7FADE10580C38C0