An Introduction to the Kalman Filter
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Citations
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Prognostic modelling options for remaining useful life estimation by industry
Methods and systems for robotic instrument tool tracking with adaptive fusion of kinematics information and image information
Information fusion for wireless sensor networks: Methods, models, and classifications
Closed-Loop Turbulence Control: Progress and Challenges
References
Superior augmented reality registration by integrating landmark tracking and magnetic tracking
Filtering for stochastic processes with applications to guidance
Virtual Reality: Scientific and Technological Challenges
Quaternion kinematic and dynamic differential equations
Related Papers (5)
Frequently Asked Questions (2)
Q2. What have the authors stated for future works in "Design and rule base reduction of a fuzzy ®lter for the estimation of motor currents" ?
The fuzzy estimator o ers the possibility of training if a nominal current history is known a priori. Further work on the topic of this paper is focusing on optimization methods that do better at ®nding the global minimum ( e. g., genetic algorithms ), integration of the ®ltering scheme with motor control, and real time implementation issues. It is not di cult to program a general purpose rule base reduction algorithm if the authors can make the following assumptions: ( 1 ) There are an odd number of membership functions for the two inputs and the output ; ( 2 ) the membership functions are symmetric triangles ; and ( 3 ) they desire to keep the two largest singular values in the R matrix of Eq. ( 56 ). A MATLAB m-®le for rule base reduction ( based on the algorithms presented in [ 10 ] and summarized here ) of a general two-input, oneoutput fuzzy logic system can be downloaded from http: //csaxp. csuohio. edu/ simon/reduce/.