Tag: Markovian

Free Download Effective Non-Hermiticity and Topology in Markovian Quadratic Bosonic Dynamics
English | 2024 | ISBN: 3031520440 | 259 Pages | PDF EPUB (True) | 20 MB
This thesis provides an in-depth investigation of effective non-Hermiticity and topology in many-mode, non-interacting, bosonic systems. It also establishes the extent to which one must move beyond the Hamiltonian, closed-system setting, in order to uncover signatures of genuine symmetry-protected topological (SPT) physics in "free" (mean-field) bosons. While SPT phases of free fermionic matter and their associated zero-energy boundary-localized modes have been thoroughly explored, similar physics in free bosonic systems still remains elusive. No fermionic counterpart exists for the distinctive dynamical behavior that arises from the effective non-Hermiticity, intrinsic even at equilibrium, to bosonic Hamiltonians. Therefore, a much needed paradigm shift is required to address major conceptual roadblocks in the search for SPT bosonic phases.

Free Download Synchronization Control of Markovian Complex Neural Networks with Time-varying Delays
English | 2024 | ISBN: 3031478347 | 271 Pages | PDF EPUB (True) | 26 MB
This monograph studies the synchronization control of Markovian complex neural networks with time-varying delays, and the structure of the book is summarized as follows. Chapter 1 introduces the system description and some background knowledges, and also addresses the motivations of this monograph. In Chapter 2, the stochastic synchronization issue of Markovian coupled neural networks with partially unknown transition rates and random coupling strengths is investigated. In Chapter 3, the local synchronization issue of Markovian neutral complex networks with partially information of transition rates is investigated. The new delay-dependent synchronization criteria in terms of LMIs are derived, which depends on the upper and lower bounds of the delays. In Chapter 4, the local synchronization issue of Markovian nonlinear coupled neural networks with uncertain and partially unknown transition rates is investigated. The less conservative local synchronization criteria containing the bounds of delay and delay derivative are obtained based on the novel augmented Lyapunov-Krasovskii functional and a new integral inequality. In Chapter 5, the sampled-data synchronization issue of delayed complex networks with aperiodic sampling interval is investigated based on enhanced input delay approach, which makes full use of the upper bound of the variable sampling interval and the sawtooth structure information of varying input delay. In Chapter 6, the sampled-data synchronization issue of Markovian coupled neural networks with mode-dependent interval time-varying delays and aperiodic sampling intervals is investigated based on an enhanced input delay approach. Furthermore, the mode-dependent sampled-data controllers are proposed based on the delay dependent synchronization criteria. In Chapter 7, the synchronization issue of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. In Chapter 8, we conclude the monograph by briefly summarizing the main theoretical findings.