# dotprod

Dot product weight function

## Syntax

```Z = dotprod(W,P,FP) dim = dotprod('size',S,R,FP) dw = dotprod('dw',W,P,Z,FP) info = dotprod('code') ```

## Description

Weight functions apply weights to an input to get weighted inputs.

`Z = dotprod(W,P,FP)` takes these inputs,

 `W ` `S`-by-`R` weight matrix `P` `R`-by-`Q` matrix of `Q` input (column) vectors `FP` Struct of function parameters (optional, ignored)

and returns the `S`-by-`Q` dot product of `W` and `P`.

`dim = dotprod('size',S,R,FP)` takes the layer dimension `S`, input dimension `R`, and function parameters, and returns the weight size [`S`-by-`R`].

`dw = dotprod('dw',W,P,Z,FP)` returns the derivative of `Z` with respect to `W`.

`info = dotprod('code')` returns information about this function. The following codes are defined:

 `'deriv'` Name of derivative function `'pfullderiv'` Input: reduced derivative = 2, full derivative = 1, linear derivative = 0 `'wfullderiv'` Weight: reduced derivative = 2, full derivative = 1, linear derivative = 0 `'name'` Full name `'fpnames'` Returns names of function parameters `'fpdefaults'` Returns default function parameters

## Examples

Here you define a random weight matrix `W` and input vector `P` and calculate the corresponding weighted input `Z`.

```W = rand(4,3); P = rand(3,1); Z = dotprod(W,P) ```

## Network Use

You can create a standard network that uses `dotprod` by calling `feedforwardnet`.

To change a network so an input weight uses `dotprod`, set `net.inputWeights{i,j}.weightFcn` to `'dotprod'`. For a layer weight, set `net.layerWeights{i,j}.weightFcn` to `'dotprod'`.

In either case, call `sim` to simulate the network with `dotprod`.

## Version History

Introduced before R2006a