# evaluate

Evaluate a neural state-space system for a given set of state and input values and return state derivative (or next state) and output values

*Since R2022b*

## Syntax

## Description

### Continuous-time

`[`

evaluates the state and output networks of the autonomous time-invariant neural
state-space system `dxdt`

,`y`

] = evaluate(`nss`

,`x`

)`nss`

at state `x`

, and returns
the time-derivative of the state `dxdt`

and the output
`y`

.

`[`

evaluates the state and output networks of the time-invariant neural state-space system
`dxdt`

,`y`

] = evaluate(`nss`

,`x`

,`u`

)`nss`

with input `u`

.

`[`

evaluates the state and output networks of the autonomous time-varying neural state-space
system `dxdt`

,`y`

] = evaluate(`nss`

,`t`

,`x`

)`nss`

at time `t`

.

`[`

evaluates the state and output networks of the time-varying neural state-space system
`dxdt`

,`y`

] = evaluate(`nss`

,`t`

,`x`

,`u`

)`nss`

at time `t`

.

### Discrete-time

`[`

evaluates the state and output networks of the autonomous time-invariant neural
state-space system `xNext`

,`y`

] = evaluate(`nss`

,`x`

)`nss`

at state `x`

, and returns
the next state `xNext`

and the output `y`

.

`[`

evaluates the state and output networks of the time-invariant neural state-space system
`xNext`

,`y`

] = evaluate(`nss`

,`x`

,`u`

)`nss`

with input `u`

.

`[`

evaluates the state and output networks of the autonomous time-varying neural state-space
system `xNext`

,`y`

] = evaluate(`nss`

,`t`

,`x`

)`nss`

at time `t`

.

`[`

evaluates the state and output networks of the time-varying neural state-space system
`xNext`

,`y`

] = evaluate(`nss`

,`t`

,`x`

,`u`

)`nss`

at time `t`

.

## Examples

## Input Arguments

## Output Arguments

## Version History

**Introduced in R2022b**

## See Also

### Objects

`idNeuralStateSpace`

|`nssTrainingADAM`

|`nssTrainingSGDM`

|`nssTrainingRMSProp`

|`nssTrainingLBFGS`

|`idss`

|`idnlgrey`

### Functions

`idNeuralStateSpace/linearize`

|`createMLPNetwork`

|`setNetwork`

|`nssTrainingOptions`

|`nlssest`

|`generateMATLABFunction`

|`sim`