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Minimum of single and multivariable functions, nonnegative least-squares, roots of nonlinear functions

Optimizers find the location of a minimum of a nonlinear objective function. You can find a minimum of a function of one variable on a bounded interval using fminbnd, or a minimum of a function of several variables on an unbounded domain using fminsearch. Maximize a function by minimizing its negative.

Find a nonnegative solution to a linear least-squares problem using lsqnonneg.

The equation solver fzero finds a real root of a nonlinear scalar function.

Control the output or other aspects of your optimization by setting options using optimset.


fminbnd Find minimum of single-variable function on fixed interval
fminsearch Find minimum of unconstrained multivariable function using derivative-free method
lsqnonneg Solve nonnegative linear least-squares problem
fzero Root of nonlinear function
optimget Optimization options values
optimset Create or edit optimization options structure


Optimizing Nonlinear Functions

Minimizing and maximizing in one or more dimensions.

Curve Fitting via Optimization

This example shows how to fit a nonlinear function to data by minimizing the sum of squared errors.

Set Options

Controlling an optimization, displaying intermediate calculations.

Iterative Display

Obtain intermediate output.

Output Functions

Describes how to monitor or halt solvers.

Plot Functions

Describes how to monitor solvers visually.

Roots of Scalar Functions

Solving a nonlinear scalar equation.

Troubleshooting and Tips

How to address common issues.

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