# Documentation

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# Nonlinear Least Squares (Curve Fitting)

Solve nonlinear least-squares (curve-fitting) problems in serial or parallel

## Functions

 `lsqcurvefit` Solve nonlinear curve-fitting (data-fitting) problems in least-squares sense `lsqnonlin` Solve nonlinear least-squares (nonlinear data-fitting) problems

## Topics

### Nonlinear Least Squares Solutions

lsqnonlin with a Simulink Model

Example of fitting a simulated model.

Nonlinear Least Squares With and Without Jacobian

Example showing the use of analytic derivatives in nonlinear least squares.

Nonlinear Curve Fitting with lsqcurvefit

Example showing how to do nonlinear data-fitting with lsqcurvefit.

Fit a Model to Complex-Valued Data

Example showing how to solve a nonlinear least-squares problem that has complex-valued data.

### Parallel Computing

What Is Parallel Computing in Optimization Toolbox?

Using multiple processors for optimization.

Using Parallel Computing in Optimization Toolbox

Automatic gradient estimation in parallel.

Improving Performance with Parallel Computing

Considerations for speeding optimizations.

### Algorithms and Options

Least-Squares (Model Fitting) Algorithms

Minimizing a sum of squares in n dimensions with only bound or linear constraints.

Optimization Options Reference

Describes optimization options.

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