... robust adversarial examples . In : International Conference on Machine Learning , pp . 284–293 . PMLR ( 2018 ) 3. Bose , J. , et al .: Adversarial example games . Adv . Neural ... Towards robust neural networks via close - loop control ...
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking.
Some theories of artificial intelligence (AI) are now showing how complex machine systems should mimic human cognitive and biological processes to improve their capabilities for dealing with uncertainty.This book bridges the gap between ...
... to guarantee stability of the closed - loop system in reference [ 176 ] . The second approach exploits the characteristics of the nonlinear activation functions commonly used in deep neural networks . Since these functions often satisfy ...
... , LNCS 3972 , pp . 904–910 , 2006 . © Springer - Verlag Berlin Heidelberg 2006 In this paper , similar to the nominal models in Robust H ∞ Control for Delayed Nonlinear Systems Based on Standard Neural Network Models Mei-Qin Liu.
Patrick K. Simpson. To improve the open - loop neural inverse control , we introduce here the concept of closed - loop robust ... network inverse and the ... via computer simulation , we used a recurrent neural network trained using ...
... via a genetic algorithm (GA). For the purpose of on-line tuning the weighting parameters of the fuzzy-neural controller, a Lyapunov-based fitness function of the GA is ... Neural Control for a Class of MIMO Systems Introduction.
... networks to robust pole assignment is proposed via convex reformulation . As spectral condition number is quasi ... control system as follows : x ( t ) = Ax ( t ) + Bu ( t ) , x ( 0 ) = xo , ( 1 ) where x ЄR " is the state vector ...
... system are discussed , along with simulation issues . Preliminary experimental data from the dynamic fixture are also presented . N95-29241 Arizona Univ . , Tucson , AZ . CLOSED LOOP CONTROL OF GUIDED MISSILES USING NEURAL NETWORKS Ph.D ...
... via the feedback control mechanism (Fig. 1), although it introduces in the issues of high cost (the use of sensors), system complexity (implementation and safety) ... Robust Adaptive Wavelet Neural Network Control of Buck Converters.