How Calculations Happen in a Neural Network

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In the previous article, we discussed how action potentials are defined.

Let's take a simple example and plot a graph.

Using Softplus as the Activation Function

For our initial example of dosage, we can take Softplus as an activation function.

Now let's find the dosage and y values based on the formula:

( Dosage x -34.4 ) + 2.14

For dosage : 0
( 0 x -34.4 ) + 2.14 = 2.14

For dosage : 0.1
( 0.1 x -34.4 ) + 2.14 = -3.44 + 2.14 = -1.3

Now let's multiply all the values calculated in the top-most hidden layer with -1.3.

For dosage : 0
2.14 x -1.3 = -2.782

For dosage : 0.1
-1.3 x -1.3 = 1.69

Similar calculations can be done for the top-most node values.

Calculating the Bottom Node

Now for the bottom-most node:

( Dosage x -2.52 ) + 1.29

For dosage : 0
( 0 x -2.52 ) + 1.29 = 1.29

For dosage : 0.1
( 0.1 x -2.52 ) + 1.29 = -0.252 + 1.29 = 1.038

Now multiply all the values calculated in the bottom-most hidden layer with 2.28.

For dosage : 0
1.29 x 2.28 = 2.94

For dosage : 0.1
1.038 x 2.28 = 2.366

Combining Both Node Results

From both the top and bottom node results, we add them together.

Finally, we subtract 0.5690 from the final value.

Here is the final prediction made by the neural network.

Weights Used in the Neural Network

These are the weights:

Bias Values Used in the Neural Network

These are the bias values:

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