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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
TLDR
Equipped with the global directional matching module and the directional appearance model learning module, DDEAL learns static cues from the labeled first frame and dynamically updates cues of the subsequent frames for object segmentation without using online fine-tuning. Expand
Adaptive Dynamic Programming: An Introduction
TLDR
Some recent research trends within the field of adaptive/approximate dynamic programming (ADP), including the variations on the structure of ADP schemes, the development of ADPs algorithms and applications, and many recent papers have provided convergence analysis associated with the algorithms developed. Expand
Reinforcement Learning and Approximate Dynamic Programming for Feedback Control
feedback control of dynamic systems 6th solution PDF feedback control of dynamic systems 6th solutions PDF feedback control of dynamic systems 5th edition pdf PDF feedback control of dynamic systemsExpand
Stability analysis of state-space realizations for two-dimensional filters with overflow nonlinearities
We utilize the second method of Lyapunov to establish sufficient conditions for the global asymptotic stability of the trivial solution of percent nonlinear, shift-invariant 2-D (two-dimensional)Expand
An adaptive algorithm for call admission control in wireless networks
  • Y. Zhang, Derong Liu
  • Computer Science
  • GLOBECOM'01. IEEE Global Telecommunications…
  • 25 November 2001
TLDR
An adaptive algorithm for call admission control in wireless networks is developed that guarantees that the handoff blocking rate is below its given threshold and at the same time, minimizes the new call blocking rate. Expand
Neural networks for modeling and control of dynamic systems: a practitioner's handbook: M. Nørgaard, O. Ravn, N.K. Poulsen, and L.K. Hansen; Springer, London, 2000, 246pp., paperback, ISBN
  • Derong Liu
  • Philosophy, Computer Science
  • Autom.
  • 1 September 2002
TLDR
Neural Networks for Modeling and Control of Dynamic Systems deals with control problems of unknown nonlinear dynamical systems using neural networks and introduces in detail the feedforward neural network structure, which is termed as multilayer perceptron networks in this book. Expand
Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems
  • Derong Liu, Q. Wei
  • Computer Science, Medicine
  • IEEE Transactions on Neural Networks and Learning…
  • 1 March 2014
TLDR
It is shown that the iterative performance index function is nonincreasingly convergent to the optimal solution of the Hamilton-Jacobi-Bellman equation and it is proven that any of the iteratives control laws can stabilize the nonlinear systems. Expand
Neural network-based model reference adaptive control system
TLDR
An approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems and results showing the feasibility and performance are given. Expand
Asymptotic stability of discrete-time systems with saturation nonlinearities with applications to digital filters
New results for an established for the global asymptotic stability of the equilibrium x=0 of nth order discrete-time systems with state saturations, x(k+1)=sat(Ax(k)), utilizing a class of positiveExpand
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