A Novel Method of Extending the Linearity Range of Linear Variable Differential Transformer Using Artificial Neural Network

2010 ◽  
Vol 59 (4) ◽  
pp. 947-953 ◽  
Author(s):  
S.K. Mishra ◽  
G. Panda ◽  
D.P. Das
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Linear Variable Differential Transformer ◽  
Linearity Range ◽  
Novel Method ◽  
Artificial Neural

A Novel Method for Diagnosing Cirrhosis in Patients with Chronic Hepatitis B: Artificial Neural Network Approach

2009 ◽  
Vol 35 (1) ◽  
pp. 121-126 ◽  
Author(s):  
Mohammad Reza Raoufy ◽  
Parviz Vahdani ◽  
Seyed Moayed Alavian ◽  
Sahba Fekri ◽  
Parivash Eftekhari ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Chronic Hepatitis ◽  
Hepatitis B ◽  
Chronic Hepatitis B ◽  
Network Approach ◽  
Neural Network Approach ◽  
Novel Method ◽  
Artificial Neural ◽  
Artificial Neural Network Approach

A novel method for telescope polarization modeling based on an artificial neural network

2021 ◽  
Vol 21 (7) ◽  
pp. 159
Author(s):  
Jian-Guo Peng ◽  
Shu Yuan ◽  
Kai-Fan Ji ◽  
Zhi Xu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Novel Method ◽  
Artificial Neural

Study on Fault Signal Detection for PMLSM

2011 ◽  
Vol 84-85 ◽  
pp. 442-446
Author(s):  
Bao Yu Xu ◽  
Xiao Zhuo Xu ◽  
Yi Lun Liu ◽  
Xu Dong Wang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wavelet Transform ◽  
Fault Detection ◽  
Frequency Band ◽  
Relative Energy ◽  
Normalization Method ◽  
Current Signal ◽  
Novel Method ◽  
Artificial Neural

Based on wavelet transform and artificial neural network, a novel method which takes advantage of both the multi-resolution decomposition of wavelet transform and the classification characteristics of artificial neural network is proposed for fault detection of permanent magnet linear synchronous motor (PMLSM). According to the characteristic of unhealthy PMLSM, the wavelet transform is carried out to decompose and reconstruct winding current signal. Then the energy of each frequency band as faulty features can be detected through spectrum analysis of wavelet coefficients about each frequency band. With normalization method, the feature vectors are constructed from relative energy for energy of each frequency band. The proposed method is applied to the fault detection of PMLSM, and the result of simulation proved that the wavelet neural network can effectively detect different conditions of PMLSM.

Artificial Neural Network as a Novel Method to Optimize Pharmaceutical Formulations

1999 ◽  
Vol 16 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Kozo Takayama ◽  
Mikito Fujikawa ◽  
Tsuneji Nagai
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Pharmaceutical Formulations ◽  
Novel Method ◽  
Artificial Neural
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