Artificial Neuron

A neuron is a unit for computation in ANN. An ANN is nothing but a large network of neurons. There are different types of neurons, and there are many types of connections between neurons. All these varieties make different kinds of deep neural networks, some work well for tabular data, others work for images, and some work for sequential data like texts or speech.

Here is the anatomy of a neuron in ANN.

Let us suppose the input has n features. So the input is like (X1, X2, X3... Xn). When this input data (more precisely a tensor) is given to the neural network, each of the features is multiplied by a weight. Then, all of them are summed up along with an additional bias value. This sum is the output of the neuron. Most of the time, to control this sum, an activation function is used. We will go through all of these in more detail.

$a_1=X_1\ast W_1$

$a_2=X_2\ast W_2$

$a_3=X_3\ast W_3$

$...$

$a_n=X_n\ast W_n$

The above can be written as:

$a_i=X_i\ast W_i;i\in \{1,\mathrm{2..}n\}$