Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.6 |
FileSize | 130660 |
MD5 | E7411B311C2D2EA99FEC57824CF212CD |
SHA-1 | 57D0BB0D866910AF5BDDA78300BE2850B9AD117D |
SHA-256 | 6EB5D4F9794FD9D7AD7F0F04384887A34A670AF6205BEE19726C9F2322CBB008 |
SSDEEP | 3072:yH8sfh43BCYpsv/q9KQCFtgTeV1xut4x9sl+3+5quZeSKvvri/z:yHYdps695CFtgTAfut4x9sli+5quUvrs |
TLSH | T1A1D33A45F782A5B0E1D310F0025F36AB23201605B177F5B3F7C67B95A87A6923A9B339 |
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 | C26B0DAE8BC60D8E8AA106D69F3BD45F |
PackageArch | i686 |
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 | EF49112733544BB0309AB1B4A10735934B70F098 |
SHA-256 | 8E6ED717135570A22E2ABDF19CB8203713186188A254C6DB9C0666F72C053547 |