TY - CHAP AU - Ivan N. da Silva AU - Wagner C. Amaral AU - Lucia V. Arruda AU - Rogerio A. Flauzino ED - Xiaolin Hu ED - P. Balasubramaniam Y1 - 2008-09-01 PY - 2008 T1 - Recurrent Neural Approach for Solving Several Types of Optimization Problems N2 - The concept of neural network originated from neuroscience, and one of its primitive aims is to help us understand the principle of the central nerve system and related behaviors through mathematical modeling. The first part of the book is a collection of three contributions dedicated to this aim. The second part of the book consists of seven chapters, all of which are about system identification and control. The third part of the book is composed of Chapter 11 and Chapter 12, where two interesting RNNs are discussed, respectively.The fourth part of the book comprises four chapters focusing on optimization problems. Doing optimization in a way like the central nerve systems of advanced animals including humans is promising from some viewpoints. BT - Recurrent Neural Networks SP - Ch. 11 UR - https://doi.org/10.5772/5544 DO - 10.5772/5544 SN - PB - IntechOpen CY - Rijeka Y2 - 2024-03-28 ER -