Neuralnum
Neuralnum is a term that refers to the representation of numerical data within artificial neural networks. It describes how numbers are encoded and processed by the network's nodes and connections. Unlike traditional computer programming where numbers are stored in specific data types like integers or floating-point numbers, neural networks typically represent numbers as activation values of neurons. These activation values are usually continuous and range between 0 and 1, or -1 and 1, depending on the activation function used.
The process of converting external numerical data into a format suitable for a neural network is called
The internal representation of numbers within the network is dynamic. As the network learns, the weights and