Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.6 |
FileSize | 130772 |
MD5 | 39895484E38108C60F00B0A33E2668CD |
SHA-1 | 1C963E2339EE2E0B015B441A0BAD632B8FC9255B |
SHA-256 | 220136DB9A503D41671FFE5326A1B76C3D9CDEE3BDE0E4FF5FD11369FC8C982B |
SSDEEP | 3072:kd4n+253lQ31HM2C002fhdPmIrmSdt+xtmU4WFuM6RUHIeRonuXIeSCNc+Jc:kd4+W2C002fhZTmSdqtmU4iuM6RUHxRw |
TLSH | T1C9D32B45F78295B0E1D300F1065F76AB222016056177F5B3FBC6AB94B87E6923E8B339 |
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 | A4A2CE2BE3DD668575CE6AD5292E937B |
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 | 7.fc34 |
PackageVersion | 2.6 |
SHA-1 | 46A7A3CCCE2385169886F12F5379207BDF649B7D |
SHA-256 | 564577DCA62BDF943A518ECF4E542AA29E3290FA109B217E8B72F64F007B0AEB |