Results 61 to 70 of about 16,203 (266)

IMPROVING THE EFFICIENCY OF THE PROCEDURE OF LYAPUNOV SPLINE-FUNCTIONS CONSTRUCTION FOR NONLINEAR NONSTATIONARY SYSTEMS

Российский технологический журнал, 2018
The paper proposes a numerical algorithm for constructing Lyapunov functions for investigating the absolute stability of nonlinear nonstationary systems.
V. P. Berdnikov
doaj   +1 more source

On the Lyapunov Exponent of Monotone Boolean Networks ^†

Mathematics, 2020
Boolean networks are discrete dynamical systems comprised of coupled Boolean functions. An important parameter that characterizes such systems is the Lyapunov exponent, which measures the state stability of the system to small perturbations.
Ilya Shmulevich
doaj   +1 more source

Complexity Analysis of Bubble Plumes in Power Law Fluids Based on Chaos Theory

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT In order to reveal the complexity of the internal flow of bubble plume in power law fluid, the flow characteristics and chaotic characteristics of plume are studied by experiment and theory. The chaotic characteristic parameters (correlation dimension D, K entropy, and Lyapunov exponent λ) of gas velocity under different superficial gas ...
Xin Dong, Chong Dong, Can Xue, Meiheng Peng, Ying Feng, Jianwei Zhang, Yinuo Liu   +6 more
wiley   +1 more source

Distributed wireless network resource optimisation method based on mobile edge computing

IET Networks, EarlyView., 2022
This paper mainly compares the network ranking leader, consumption amount and network signal reception of the three algorithms. The study found that in terms of network sort captain, there are significant differences between the CPLEX algorithm, the CCST algorithm, and edge computing methods. The CCST algorithm and edge computing have little difference
Jiongting Jiang, Chao Quan, Kai Qian, Jiefeng Pan, Yueping Yang   +4 more
wiley   +1 more source

Artificial Neural Network Driven Computational Modeling of Naegleria fowleri Epidemics Using Variational Optimization

Advanced Physics Research, EarlyView.
ABSTRACT This study presents a mathematical framework to analyze the transmission dynamics of an amoeba‐induced central nervous system infection. The population is divided into compartments including susceptible, exposed, infected, quarantined, hospitalized, recovered, protected, and deceased.
Wakeel Ahmed, Areej Yaseen, Ghulamullah Saeedi, Shakeel Ahmed   +3 more
wiley   +1 more source

Separable Lyapunov functions for monotone systems

, 2013
Separable Lyapunov functions play vital roles, for example, in stability analysis of large-scale systems. A Lyapunov function is called max-separable if it can be decomposed into a maximum of functions with one-dimensional arguments.
Gunther Dirr, Rantzer, Anders, Bjorn S. Ruffer, Anders Rantzer, Rüffer, Björn, Dirr, Gunther   +5 more
core   +2 more sources

Lipschitz Stability for Non-Instantaneous Impulsive Caputo Fractional Differential Equations with State Dependent Delays

Axioms, 2018
In this paper, we study Lipschitz stability of Caputo fractional differential equations with non-instantaneous impulses and state dependent delays. The study is based on Lyapunov functions and the Razumikhin technique. Our equations in particular include
Ravi Agarwal, Snezhana Hristova, Donal O'Regan   +2 more
doaj   +1 more source

Approximation of Lyapunov functions from noisy data [PDF]

, 2019
Methods have previously been developed for the approximation of Lyapunov functions using radial basis functions. However these methods assume that the evolution equations are known. We consider the problem of approximating a given Lyapunov function using
Giesl, Peter, Hamzi, Boumediene, Webster, Kevin N, Peter Giesl (4462135), Martin Rasmussen (11907929), Rasmussen, Martin, Boumediene Hamzi (16277240), Kevin Webster (15042242)   +7 more
core   +1 more source

Risk‐aware safe reinforcement learning for control of stochastic linear systems

Asian Journal of Control, EarlyView.
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili, Nariman Niknejad, Hamidreza Modares   +2 more
wiley   +1 more source

Safe deep reinforcement learning method for guaranteed compliance with physical constraints in autonomous energy systems of critical infrastructure (a case study of healthcare facilities)

Авіаційно-космічна техніка та технологія
The study examines the complex processes of intelligent management of energy resilience in modern healthcare facilities during critical situations, large-scale failures, and prolonged outages of the external centralized power supply.
Maksym Kushnarov
doaj   +1 more source