Delay-Dependent Guaranteed Cost Controller Design for Uncertain Neural Networks with Interval Time-Varying Delay

This paper studies the problem of guaranteed cost control for a class of uncertain delayed neural networks. The time delay is a continuous function belonging to a given interval but not necessary to be differentiable. A cost function is considered as a nonlinear performance measure for the closed-loop system. The stabilizing controllers to be designed must satisfy some exponential stability constraints on the closed-loop poles. By constructing a set of augmented Lyapunov-Krasovskii functionals combined with Newton-Leibniz formula, a guaranteed cost controller is designed via memoryless state feedback control, and new sufficient conditions for the existence of the guaranteed cost state feedback for the system are given in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the effectiveness of the obtained result

Anti-bacterial activity of inorganic nanomaterials and their antimicrobial peptide conjugates against resistant and non-resistant pathogens

This review details the antimicrobial applications of inorganic nanomaterials of mostly metallic form, and the augmentation of activity by surface conjugation of peptide ligands. The review is subdivided into three main sections, of which the first describes the antimicrobial activity of inorganic nanomaterials against gram-positive, gram-negative and multidrug-resistant bacterial strains. The second section highlights the range of antimicrobial peptides and the drug resistance strategies employed by bacterial species to counter lethality. The final part discusses the role of antimicrobial peptide-decorated inorganic nanomaterials in the fight against bacterial strains that show resistance. General strategies for the preparation of antimicrobial peptides and their conjugation to nanomaterials are discussed, emphasizing the use of elemental and metallic oxide nanomaterials. Importantly, the permeation of antimicrobial peptides through the bacterial membrane is shown to aid the delivery of nanomaterials into bacterial cells. By judicious use of targeting ligands, the nanomaterial becomes able to differentiate between bacterial and mammalian cells and, thus, reduce side effects. Moreover, peptide conjugation to the surface of a nanomaterial will alter surface chemistry in ways that lead to reduction in toxicity and improvements in biocompatibility

Synchronization of Fractional Order Uncertain BAM Competitive Neural Networks

This article examines the drive-response synchronization of a class of fractional order uncertain BAM (Bidirectional Associative Memory) competitive neural networks. By using the differential inclusions theory, and constructing a proper Lyapunov-Krasovskii functional, novel sufficient conditions are obtained to achieve global asymptotic stability of fractional order uncertain BAM competitive neural networks. This novel approach is based on the linear matrix inequality (LMI) technique and the derived conditions are easy to verify via the LMI toolbox. Moreover, numerical examples are presented to show the feasibility and effectiveness of the theoretical results

Synchronization of Fractional Order Uncertain BAM Competitive Neural Networks

This article examines the drive-response synchronization of a class of fractional order uncertain BAM (Bidirectional Associative Memory) competitive neural networks. By using the differential inclusions theory, and constructing a proper Lyapunov-Krasovskii functional, novel sufficient conditions are obtained to achieve global asymptotic stability of fractional order uncertain BAM competitive neural networks. This novel approach is based on the linear matrix inequality (LMI) technique and the derived conditions are easy to verify via the LMI toolbox. Moreover, numerical examples are presented to show the feasibility and effectiveness of the theoretical results