Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2.6 |
FileSize | 135784 |
MD5 | 978B6C78460B967C7AC735F8CFD01032 |
SHA-1 | 3336971B3E14F0C0042732D29E3EB393E6A0FF3E |
SHA-256 | 7DD841CA4FA4D4BA4130211057C805DF3B2EFBD76CEB2449DCC1BEAAE402B24D |
SSDEEP | 3072:NdMqTVN/M9ppRiXczgXOpMdEJkHxeSCD:fMqTVN/M9wXczgXO2CaxdE |
TLSH | T158D37D49FE0F6852C1C1F3B8A74D4A58733A2250F75670F32403D3EC5A46BAADAE7664 |
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 | 536B647C8AD64C48B8D1FC0CDC989EB4 |
PackageArch | aarch64 |
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 | FA12421AE62573AC2931C1697C09C6AA20DDC2CE |
SHA-256 | 352284E32FFA62C8D0181E175ACFDF8481772276725451FE28C505EB9CAA9A38 |