|
|
|
|
|
Marek Kciuk, Zygmunt Kowalik, Grazia Lo Sciuto, Sebastian Slawski and Stefano Mastrostefano
The promising research on flexible and tactile sensors requires conducting polymer materials and an accurate system for the transduction of pressure into electrical signals. In this paper, the intelligent sensitive mat, based on Velostat, which is a poly...
ver más
|
|
|
|
|
|
|
|
|
Daniel S. Soper
When designed correctly, radial basis function (RBF) neural networks can approximate mathematical functions to any arbitrary degree of precision. Multilayer perceptron (MLP) neural networks are also universal function approximators, but RBF neural networ...
ver más
|
|
|
|
|
|
|
|
|
Jiayu Wen, Yanguo Song, Huanjin Wang, Dong Han and Changfa Yang
Neural networks have been widely used as compensational models for aircraft control designs and as surrogate models for other optimizations. In the case of tiltrotor aircraft, the total number of aircraft states and controls is much greater than that of ...
ver más
|
|
|
|
|
|
|
|
|
Chunyi Zhang, Zheshan Yuan, Huan Li, Jiongran Wen, Shengkai Zheng and Chengwei Fei
To enhance the accuracy and efficiency of reliability analysis for an aero-engine vectoring exhaust nozzle (VEN), a multi-extremum adaptive fuzzy network (MEAFN) method is developed by absorbing an adaptive neuro-fuzzy inference system (ANFIS) into the m...
ver más
|
|
|
|
|
|
|
|
|
Gaoyuan Cai, Juhu Li, Xuanxin Liu, Zhibo Chen and Haiyan Zhang
Recently, the deep neural network (DNN) has become one of the most advanced and powerful methods used in classification tasks. However, the cost of DNN models is sometimes considerable due to the huge sets of parameters. Therefore, it is necessary to com...
ver más
|
|
|
|