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
收藏
页码：124 / 127
页数：4
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