# Highly connected dynamic artificial neural networks

arXiv: https://arxiv.org/abs/2302.08928 · HTML: https://mlsanity.com/paper/2302.08928/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 1 references that are in the map.
- First posted on arXiv 17 Feb 2023.

## Built on by (most cited first, 1 of 1)

- [Fuzzy Feature Selection with Key-based Cryptographic Transformations](https://mlsanity.com/paper/2306.09583/) (2023)

## Abstract (arXiv)

An object-oriented approach to implementing artificial neural networks is introduced in this article. The networks obtained in this way are highly connected in that they admit edges between nodes in any layers of the network, and dynamic, in that the insertion, or deletion, of nodes, edges or layers of nodes can be effected in a straightforward way. In addition, the activation functions of nodes need not be uniform within layers, and can also be changed within individual nodes. Methods for implementing the feedforward step and the backpropagation technique in such networks are presented here. Methods for creating networks, for implementing the various dynamic properties and for saving and recreating networks are also described.