Title :
Comparison of neural network and extended Kalman filter determination of kinematics from impact acceleration tests
Author :
Bashi, Anwer S. ; Kaminsky, Edit J.
Author_Institution :
Dept. of Electr. Eng., New Orleans Univ., LA, USA
Abstract :
This paper compares the performance of an artificial neural network (ANN) with that of an extended Kalman filter (EKF) for use in processing accelerometer data collected during impact acceleration tests. Both the EKF and the ANN are required to produce subject kinematics from the noisy readings. The ANN is much simpler to implement, and gives desirable results. Moreover, the ANN implementation, unlike the EKF implementation, does not require a model of the system
Keywords :
Kalman filters; acceleration measurement; accelerometers; computerised instrumentation; kinematics; neural nets; performance evaluation; testing; accelerometer data processing; extended Kalman filter; impact acceleration tests; kinematics; neural network; noisy readings; performance; Acceleration; Accelerometers; Artificial neural networks; Kinematics; Laboratories; Life estimation; Neural networks; Quaternions; Sensor arrays; Testing;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.633194
