Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks

By Lee A. Feldkamp, Danil V. Prokhorov, T. Feldkamp. 2003

67 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Laurence Aitchison
2. Dacheng Tao
3. Jun Li
4. Danil V. Prokhorov
5. Xue Mei
6. Frederik Benzing
7. Jing Zhang
8. Charu C. Aggarwal

In Control and Systems Engineering

1. Laurence Aitchison
2. Dacheng Tao
3. Danil V. Prokhorov

Citations in the corpus

• Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods (2018, methodology): “Here we formulated Bayesian inference as an optimization problem (Puskorius & Feldkamp, 1991; Sha et al., 1992; Puskorius & Feldkamp, 1994, 2001; Feldkamp et al., 2003; Ollivier, 2017), and carefully considered how optimization of the other parameters influences the optimum of our parameter of inter”
• Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene (2017, methodology): “The observed behavior is consistent with what to expect from the well-trained RNN on challenging sequence prediction tasks (see [28], [29]).”