TY  - JOUR
T1  - Parameter Based Kalman Filter Training in Neural Network
AU - JenoPaul, P. AU - SreeDevi, M. 
JO  - International Journal of Soft Computing
VL  - 8
IS  - 5
SP  - 352
EP  - 355
PY  - 2013
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2013.352.355
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2013.352.355
KW  - KF-kalman filtering
KW  -neural networks
KW  -NNs
KW  -brain
KW  -fault
AB  - Neural Networks (NNs) have been employed in many applications 
  in recent years. A neural network is an interconnection of a number of artificial 
  neurons that simulate a biological brain system. It has the ability to approximate 
  nonlinear functions and can achieve higher degree of fault tolerance. NNs have 
  been successfully introduced into power electronics circuits where a NN replaced 
  a large and memory demanding look-up table to generate the switching angles. 
  The neural network controllers for engine idle speed and Air/Fuel (A/F) ratio 
  control produce signals that affect the operation of the engine while the neural 
  network models are used to describe various aspects of engine operation as a 
  function of measurable engine outputs. This study aims to study the behavior 
  of the parameter based kalman filtering in neural network.
ER  -