# concur

Create concurrent bias vectors

## Syntax

```concur(B,Q) ```

## Description

`concur(B,Q)`

 `B` `S`-by-`1` bias vector (or an `Nl`-by-`1` cell array of vectors) `Q` Concurrent size

and returns an `S`-by-`B` matrix of copies of `B` (or an `Nl`-by-`1` cell array of matrices).

## Examples

Here `concur` creates three copies of a bias vector.

```b = [1; 3; 2; -1]; concur(b,3) ```

## Network Use

To calculate a layer’s net input, the layer’s weighted inputs must be combined with its biases. The following expression calculates the net input for a layer with the `netsum` net input function, two input weights, and a bias:

```n = netsum(z1,z2,b) ```

The above expression works if `Z1`, `Z2`, and `B` are all `S`-by-`1` vectors. However, if the network is being simulated by `sim` (or `adapt` or `train`) in response to `Q` concurrent vectors, then `Z1` and `Z2` will be `S`-by-`Q` matrices. Before `B` can be combined with `Z1` and `Z2`, you must make `Q` copies of it.

```n = netsum(z1,z2,concur(b,q)) ```