Kalman Filtering and Neural Networks - Chapter 2: PARAMETER-BASED KALMAN FILTER TRAINING: THEORY AND IMPLEMENTATION
Kalman Filtering and Neural Networks - Chapter 2: PARAMETER-BASED KALMAN FILTER TRAINING: THEORY AND IMPLEMENTATION
Although the rediscovery in the mid 1980s of the backpropagation algorithm by Rumelhart, Hinton, and Williams [1] has long been viewed as a landmark event in the history of neural network computing and has led to a sustained resurgence of activity, the relative ineffectiveness of this simple gradient method has motivated many researchers to develop enhanced training procedures. In fact, the neural network literature has been inundated with papers proposing alternative training Kalman Filtering a