calcpd (Neural Network Toolbox™)

Neural Network Toolbox™

calcpd

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Calculate delayed network inputs

Syntax

```
Pd = calcpd(net,TS,Q,Pc)
```

Description

This function calculates the results of passing the network inputs through each input weight's tap delay line.

Pd = calcpd(net,TS,Q,Pc) takes

net
Neural network

TS
Time steps

Q
Concurrent size

Pc
Combined inputs = [initial delay conditions, network inputs]

`net`	Neural network
`TS`	Time steps
`Q`	Concurrent size
`Pc`	Combined inputs = [initial delay conditions, network inputs]

and returns

Pd
Delayed inputs

`Pd`	Delayed inputs

Examples

Here is a linear network with a single input element ranging from 0 to 1, three neurons, and a tap delay on the input with taps at 0, 2, and 4 time steps.

```
net = newlin([0 1],3,[0 2 4]);
```

Here is a single (Q = 1) input sequence P with eight time steps (TS = 8).

```
P = {0 0.1 0.3 0.6 0.4 0.7 0.2 0.1};
```

Here the four initial input delay conditions Pi are defined.

```
Pi = {0.2 0.3 0.4 0.1};
```

The delayed inputs (the inputs after passing through the tap delays) can be calculated with calcpd.

```
Pc = [Pi P];
Pd = calcpd(net,8,1,Pc)
```

You can view the delayed inputs for the input weight going to layer 1 from input 1 at time steps 1 and 2.

```
Pd{1,1,1}
Pd{1,1,2}
```

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