| Key | Value |
|---|---|
| FileName | ./usr/lib64/liblevmar.so.2.6 |
| FileSize | 200848 |
| MD5 | ECD33B1FB54FFEA7F02C161DC97CA5C9 |
| SHA-1 | 0082C65769DC448417FE396186A2A4360A90CB6D |
| SHA-256 | B0A9BDD72FCA53DD7EDC6D4211151C6AD649FB5B42704F29B781D75D020A4402 |
| SSDEEP | 1536:0XwmBInXjocoGiNiKs5bp01cE04F7ebH4WVh6FObwGqhurLqKW6IlragQdZRcg:CIjVoGiNiKs5bp01cE02e0Ubqwd |
| TLSH | T142146C2733486B05DBC06C7F834D6E61B7A6394B162895E3ED40831B6E75B3ACB47A4C |
| 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 | 2D15257FBC356052C44599062442F852 |
| PackageArch | ppc64le |
| 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 | 7F674ED65E63F7584F1BDA64C9386F6322B93BD7 |
| SHA-256 | 55F29B81C321387A2F8855A438F2EFF84D39EFF75430E6CAFEF0E8F834775D9E |