# nlhw

Estimate Hammerstein-Wiener model

## Syntax

## Description

### Estimate Hammerstein-Wiener Model

specifies `sys`

= nlhw(`Data`

,`Orders`

,`InputNonlinearity`

,`OutputNonlinearity`

)`InputNL`

and `OutputNL`

as the
input and output nonlinearity estimators, respectively.

### Specify Linear Model

specifies `sys`

= nlhw(`Data`

,`LinModel`

,`InputNonlinearity`

,`OutputNonlinearity`

)`InputNonlinearity`

and
`OutputNonlinearity`

as the input and output nonlinearity
estimators, respectively.

### Refine Existing Model

refines
or estimates the parameters of a Hammerstein-Wiener model, `sys`

= nlhw(`Data`

,`sys0`

)`sys0`

,
using the estimation data.

Use this syntax to:

Update the parameters of a previously estimated model to improve the fit to the estimation data. In this case, the estimation algorithm uses the parameters of

`sys0`

as initial guesses.Estimate the parameters of a model previously created using the

`idnlhw`

constructor. Prior to estimation, you can configure the model properties using dot notation.

### Specify Options

specifies additional model estimation options using the option set
`sys`

= nlhw(___,`Options`

)`Options`

that you create using `nlhwOptions`

. Use
`Options`

with any of the previous syntaxes.

## Examples

## Input Arguments

## Output Arguments

## Extended Capabilities

## Version History

**Introduced in R2007a**

## See Also

`idnlhw`

| `nlhwOptions`

| `idnlhw/findop`

| `linapp`

| `linearize`

| `pem`

| `init`

| `oe`

| `tfest`

| `n4sid`

| `goodnessOfFit`

| `aic`

| `fpe`

### Topics

- Estimate Multiple Hammerstein-Wiener Models
- Estimate Hammerstein-Wiener Models Initialized Using Linear OE Models
- Identifying Hammerstein-Wiener Models
- Available Nonlinearity Estimators for Hammerstein-Wiener Models
- Initialize Hammerstein-Wiener Estimation Using Linear Model
- Loss Function and Model Quality Metrics
- Regularized Estimates of Model Parameters
- Estimation Report