Weight and Bias Values :: Network Object Reference (Neural Network Toolbox)

Neural Network Toolbox

Weight and Bias Values

These properties define the network's adjustable parameters: its weight matrices and bias vectors.

This property defines the weight matrices of weights going to layers from network inputs.

```
net.IW
```

It is always an cell array, where is the number of network layers (net.numLayers), and is the number of network inputs (net.numInputs).

The weight matrix for the weight going to the ith layer from the jth input (or a null matrix []) is located at

```
net.IW{i,j}
```

if the corresponding input connection is 1 (or 0).

```
net.inputConnect(i,j)
```

The weight matrix has as many rows as the size of the layer it goes to (net.layers{i}.size). It has as many columns as the product of the input size with the number of delays associated with the weight.

net.inputs{j}.size * length(net.inputWeights{i,j}.delays)

These dimensions can also be obtained from the input weight properties.

```
net.inputWeights{i,j}.size
```

This property defines the weight matrices of weights going to layers from other layers.

```
net.LW
```

It is always an cell array, where is the number of network layers (net.numLayers).

The weight matrix for the weight going to the ith layer from the jth layer (or a null matrix []) is located at

```
net.LW{i,j}
```

if the corresponding layer connection is 1 (or 0).

```
net.layerConnect(i,j)
```

The weight matrix has as many rows as the size of the layer it goes to (net.layers{i}.size). It has as many columns as the product of the size of the layer it comes from with the number of delays associated with the weight.

net.layers{j}.size * length(net.layerWeights{i,j}.delays)

These dimensions can also be obtained from the layer weight properties.

```
net.layerWeights{i,j}.size
```

This property defines the bias vectors for each layer with a bias.

```
net.b
```

It is always an cell array, where is the number of network layers (net.numLayers).

The bias vector for the ith layer (or a null matrix []) is located at

```
net.b{i}
```

if the corresponding bias connection is 1 (or 0).

```
net.biasConnect(i)
```

The number of elements in the bias vector is always equal to the size of the layer it is associated with (net.layers{i}.size).

This dimension can also be obtained from the bias properties.

```
net.biases{i}.size
```

Parameters Other