Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.6 |
FileSize | 102236 |
MD5 | C2AED064FB4A48B091BF5AC3E19AB186 |
SHA-1 | 6152FBA6695A61A95E0162D3CE4D52CACDBE8966 |
SHA-256 | B4B0059A69FF9FCC797B6D09398945A9265C88FB7171D2D333354C16BAE95C6A |
SSDEEP | 1536:8mG0p1UZExt7usrDy5Lyk2panFX+QqG9wLIp7niqSxmnaDOA:9p1UUkLyk2pandqG9o4DiqpZA |
TLSH | T177A3398ABC409FA1C8C0A6F4933E979833131BB1D3A771579016E7347BA65290F3BB49 |
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 | 141D9D0C7F36FDB9F5DA5CDE7CD66C2F |
PackageArch | armv7hl |
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 | 2.fc32 |
PackageVersion | 2.6 |
SHA-1 | D3C96CC786E3BFB862298D1CE7537359BC16CDA6 |
SHA-256 | 8860E43400B1F000B1F0D2EE2F46FBA4B391EFE2CFF9D7B5D90074976AD689AF |