HAMILTONIAN NEURAL NETWORK-BASED ORTHOGONAL FILTERS A Basis for Artificial Intelligence

被引：0

作者：

Citko, Wieslaw ^{[1
]}

Sienko, Wieslaw ^{[1
]}

机构：

[1] Gdynia Maritime Univ, Dept Elect Engn, Morska 81-86, PL-81225 Gdynia, Poland

来源：

NCTA 2011: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NEURAL COMPUTATION THEORY AND APPLICATIONS | 2011年

关键词：

Hamiltonian neural network; Machine learning; Artificial intelligence;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The purpose of the paper is to present how very large scale networks for learning can be designed by using Hamiltonian Neural Network-based orthogonal filters and in particular by using octonionic modules. We claim here that octonionic modules are basic building blocks to implement AI compatible processors.

引用

页码：124 / 127

页数：4

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