The paper studies the ability possessed by recurrent neural networks to model dynamic systems when some relevant state variables are not measurable.
The paper studies the ability possessed by recurrent neural networks to model dynamic systems when some relevant state variables are not measurable.
The paper deals with neural modelling of dynamic processes. Attention is focused on processes characterised by non-measurable states and their modelling ...
Neural architectures Conversely, when some (if not all) the state variables are based on virtual states—which naturally arise from a space state representation— ...
Neural modeling of dynamic systems with nonmeasurable state variables. Alippi, C. ;; Piuri, V. Abstract. Publication: IEEE Transactions on Instrumentation ...
@Article {TRAN1999, author = {C. Alippi, V. Piuri}, title = {Neural modeling of dynamic systems with nonmeasurable state variables}, publisher = {IEEE},
A study is performed to investigate the state evolution of a kind of recurrent neural network. The state variable in the neural system summarize the ...
Missing: nonmeasurable | Show results with:nonmeasurable
Duration: 1:06:20
Posted: Jul 27, 2023
Posted: Jul 27, 2023
Article "Neural Modeling of Dynamic Systems with Nonmeasurable State Variables." Detailed information of the J-GLOBAL is an information service managed by ...
Feb 9, 2023 · One way to leverage known relations is to calculate derivatives of state variables using automatic differentiation instead of having the network ...