For example, the calculus derivative of the hyperbolic tangent function is (1 - y)(1 + y). Because the back-propagation algorithm requires the derivative, only functions that have derivatives can be ...

Learn With Jay. Backpropagation In Neural Networks — Full Derivation Step-By-Step. Posted: May 7, 2025 | Last updated: July 11, 2025. Don’t just use backprop — understand it.

In this article, I’ll cover the theory behind one subset of the vast field of neural nets: back-propagation networks. I’ll cover the basics and the implementation of the game just described.

A back-propagation neural network can easily predict the energy consumption of a pipeline system with fewer mathematical statistics than other methods and a simple pretreatment of the original ...

More information: Giuseppe Montanaro et al, Phenotyping Key Fruit Quality Traits in Olive Using RGB Images and Back Propagation Neural Networks, Plant Phenomics (2023). DOI: 10.34133 ...

For example, the calculus derivative of the hyperbolic tangent function is (1 - y)(1 + y). Because the back-propagation algorithm requires the derivative, only functions that have derivatives can be ...