AIMC Topic: Time Factors

Clear Filters Showing 1621 to 1630 of 2001 articles

Finite-Horizon Near-Optimal Output Feedback Neural Network Control of Quantized Nonlinear Discrete-Time Systems With Input Constraint.

IEEE transactions on neural networks and learning systems
The output feedback-based near-optimal regulation of uncertain and quantized nonlinear discrete-time systems in affine form with control constraint over finite horizon is addressed in this paper. First, the effect of input constraint is handled using...

A new delay-independent condition for global robust stability of neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
This paper studies the problem of robust stability of dynamical neural networks with discrete time delays under the assumptions that the network parameters of the neural system are uncertain and norm-bounded, and the activation functions are slope-bo...

Global exponential periodicity and stability of discrete-time complex-valued recurrent neural networks with time-delays.

Neural networks : the official journal of the International Neural Network Society
In recent years, complex-valued recurrent neural networks have been developed and analysed in-depth in view of that they have good modelling performance for some applications involving complex-valued elements. In implementing continuous-time dynamica...

The 26-Minute Laparoscopic Sacral Colpopexy: Do We Really Need Robotic Technology?

Journal of minimally invasive gynecology
STUDY OBJECTIVES: To demonstrate the technical steps of a laparoscopic sacral colpopexy (LSC), demonstrate the efficiency of LSC, review the comparative LSC and robotic-assisted sacral colpopexy (RSC) literature, and challenge surgeons' conventional ...

Robotic liver surgery: preliminary experience in a tertiary hepato-biliary unit.

Updates in surgery
Minimally invasive liver surgery is performed with increasing frequency by hepatic surgeons. Laparoscopy was the first approach to be used and it is currently safely feasible in selected patients by experienced surgeons. Minor and major laparoscopic ...

Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction.

IEEE transactions on neural networks and learning systems
Collaboration enables weak species to survive in an environment where different species compete for limited resources. Cooperative coevolution (CC) is a nature-inspired optimization method that divides a problem into subcomponents and evolves them wh...

Multistability for Delayed Neural Networks via Sequential Contracting.

IEEE transactions on neural networks and learning systems
In this paper, we explore a variety of new multistability scenarios in the general delayed neural network system. Geometric structure embedded in equations is exploited and incorporated into the analysis to elucidate the underlying dynamics. Criteria...

Error bounds of adaptive dynamic programming algorithms for solving undiscounted optimal control problems.

IEEE transactions on neural networks and learning systems
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update eq...

Stochastic sampled-data control for synchronization of complex dynamical networks with control packet loss and additive time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This study examines the exponential synchronization of complex dynamical networks with control packet loss and additive time-varying delays. Additionally, sampled-data controller with time-varying sampling period is considered and is assumed to switc...