Non-linear least squares

Known as: NLS, Nonlinear least squares, NLLS 
Nonlinear least squares is the form of least squares analysis used to fit a set of m observations with a model that is non-linear in n unknown… (More)
Wikipedia

Topic mentions per year

Topic mentions per year

1966-2018
05010019662018

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2013
2013
A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the… (More)
  • figure 1
  • figure 2
  • table 1
  • table 2
  • table 2
Is this relevant?
Highly Cited
2013
Highly Cited
2013
PURPOSE Linear least squares estimators are widely used in diffusion MRI for the estimation of diffusion parameters. Although… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
2012
2012
Various estimation problems can be formulated as non-linear least squares (NLLS) problems, which can be solved using the Gauss… (More)
  • figure 1
  • figure 2
Is this relevant?
2010
2010
In measurement tasks, such as the determination of the arrival time of events, several methods based on least squares routines… (More)
  • figure 6
  • table I
Is this relevant?
Review
2010
Review
2010
Several estimation problems in vision involve the minimization of cumulative geometric error using non-linear least-squares… (More)
  • table 1
  • figure 1
  • figure 2
  • figure 3
  • table 2
Is this relevant?
2008
2008
Using measured radial velocity data of nine double lined spectroscopic binary systems NSV 223, AB And, V2082 Cyg, HS Her, V918… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
1999
1999
We consider the problem of estimating the frequency of a complex harmonic in the presence of additive and multiplicative noise… (More)
  • figure 1
  • figure 2
  • figure 3
Is this relevant?
Highly Cited
1994
Highly Cited
1994
Fitting circles and ellipses to given points in the plane is a problem that arises in many application areas, e.g. computer… (More)
  • figure 2.1
  • figure 5.1
  • figure 5.2
  • figure 6.1
  • figure 7.1
Is this relevant?
1993
1993
In this work, we propose the use of an adaptive nonlinear least-squares algorithm t o solve the inverse kinematic problem for… (More)
  • figure 2
  • figure 3
Is this relevant?
Highly Cited
1993
Highly Cited
1993
The simultaneous recovery of 3D shape and motion from image sequences is one of the more difficult problems in computer vision… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?