Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.6 |
FileSize | 127296 |
MD5 | 3FEE2721F028F48845109577539C8EA0 |
SHA-1 | C74BD1B4E3E08228C8DF1C3A86CDD705E518F30A |
SHA-256 | 60881F00E7F767105097580B4508451F97847FBDFC4B62FFA899BA9B11D821E4 |
SSDEEP | 1536:bbD4lY42bzHIMd7VyeaOAv/7fzkfSa1mWL1x90MvoofQbXfmFm7g6vpAm01na5ly:bglB2bBXw/0R30Mkbom3aB1 |
TLSH | T1A2C34BC7B9628BA6D0B42F75C3AEABB5A30B262939D13D0EDB9DD73049135106F03752 |
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 | 81CE1EFF58757A9AF5CF7E3C37318C84 |
PackageArch | s390x |
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 | 33FBCA39106B6199A7E20D215B7EEC01670B1E98 |
SHA-256 | EBD94F0AE293B2E626FFE55DB804071CD0B6FD9534E07CE019FCCF7937F437E4 |