Understanding Neural Network Architecture: Neurons in a General Neural Network

Photo by Gustavo Boaron on Unsplash

Neurons, also referred to as nodes, are the basic computational units in a neural network. They are organized into layers, and each neuron processes information and performs computations on the input data. The architecture and functioning of neurons vary based on the type of neural network.

I. Neurons in a General Neural Network:

1. Input Layer Neurons:

• Neurons in the input layer represent individual features of the input data.
• Each neuron corresponds to a specific input feature, and the values of these neurons form the input vector.

Input Layer Neurons:
+---+---+---+---+
| x1| x2| x3| x4|
+---+---+---+---+

• In the example above, each neuron (x1,x2,x3,x4) represents a distinct feature of the input.
• The values of these neurons collectively form an input vector.
• The input vector is the numerical representation of the input data that is fed into the neural network.

Input Vector:
[x1, x2, x3, x4]

• Each neuron is responsible for encoding information about a specific aspect of the input.
• For example, in an image classification…