Solve own problem using manually selected rules
The problem
Upload file:
Normalize problem
Information about noise
Upper bounds
δ =
η =
These are
relative
absolute
noise levels.
Standard deviation
σ =
σ
η
=
These are
relative
absolute
noise levels.
No information about noise is known.
Parameter choice rules
Delta-rules
Unstable delta-rules
Discrepancy principle (D)
c =
Monotone error rule (ME)
c =
ME rule with post-estimation (MEe)
γ =
c =
Adjusted monotone error rule (MEa)
Raus-Gfrerer rule (RG)
c =
Stable delta-rules
Balancing principle (BP)
c =
Rule R1
k =
c =
Rule R2(q=2, k=2, l=1/2)
c =
Rule R2(q=2, k=1, l=1/2)
c =
A priori parameter selection
A priori (Apri)
α =
Heuristic rules
Quasioptimality criterion (Q)
κ
Nb
Hanke-Raus rule (HR)
κ
Nb
Regińska's rule (Reg)
τ =
κ
Nb
Modified Regińska's rule (MReg)
κ
Nb
Hybrid rule (Hyb)
Brezinski-Rodriguez-Seatzu rule (BRS)
κ
Nb
Generalized cross-validation (GCV)
κ
Nb
Robust generalized cross-validation (RGCV)
γ =
κ
Nb
Strong robust generalized cross-validation (SRGCV)
γ =
κ
Nb
Modified generalized cross-validation (MGCV)
c =
κ
Nb
Generalized maximum likelihood method (GML)
κ
Nb
Residual method (Res)
κ
Nb
HR monotone error rule (HRME)
κ
Nb
HR(1/4) rule
κ
Nb
Technical
Parameter interval:
α
M
=
α
0
=
stepsize q =