| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1168781 | Analytica Chimica Acta | 2009 | 11 Pages |
Abstract
Artificial neural networks are a family of non-linear computational methods, loosely inspired by the human brain, that have found application in an increasing number of fields of analytical chemistry and specifically of food control. In this review, the main neural network architectures are described and examples of their application to solve food analytical problems are presented, together with some considerations about their uses and misuses.
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Federico Marini,