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.

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 ...

Neuromorphic systems can accelerate neural networks by performing multiply-accumulate operations in parallel using nonvolatile analog memory. However, executing the widely used backpropagation ...

The most common algorithm used to train feed-forward neural networks is called back-propagation. Back-propagation compares neural network actual outputs (for a given set of inputs, and weights and ...