Novel results on asymptotic stability and synchronization of fractional-order memristive neural networks with time delays: The 0<뫲1 case.

This paper investigates the asymptotic stability and synchronization of fractional-order (FO) memristive neural networks with time delays. Based on the FO comparison principle and inverse Laplace transform method, the novel sufficient conditions for the asymptotic stability of a FO nonlinear system are given. Then, based on the above conclusions, the sufficient conditions for the asymptotic stability and synchronization of FO memristive neural networks with time delays are investigated. The results in this paper have a wider coverage of situations and are more practical than the previous related results. Finally, the validity of the results is checked by two examples.

H-/H∞ fault detection observer design for fractional-order singular systems in finite frequency domains.

This paper investigates the robust fault detection observer design problem in finite frequency domains for fractional-order singular systems. An H-/H∞ fault detection observer for fractional-order singular systems is designed to meet the system admissibility, disturbance robustness and fault sensitivity indices in finite frequency domains simultaneously. Four theorems and four corollaries about the system admissibility and the performance index H-/H∞ in different frequency ranges are given, and then the sufficient conditions are obtained in terms of linear matrix inequalities. Finally, two numerical examples are given to verify the validity of the presented methods.

New Criteria on Finite-Time Stability of Fractional-Order Hopfield Neural Networks With Time Delays.

In this article, the finite-time stability (FTS) of fractional-order Hopfield neural networks with time delays (FHNNTDs) is studied. A widely used inequality in investigating the stability of the fractional-order neural networks is fractional-order Gronwall inequality related to the Mittag-Leffler function, which cannot be directly used to study the stability of the factional-order neural networks with time delays. In the existing works related to fractional-order Gronwall inequality with time delays, the order was divided into two cases: λ ∈ (0,0.5] and λ ∈ (0.5,+∞) . In this article, a new fractional-order Gronwall integral inequality with time delay and the unified form for all the fractional order is developed, which can be widely applied to investigate FTS of various fractional-order systems with time delays. Based on this new inequality, a new criterion for the FTS of FHNNTDs is derived. Compared with the existing criteria, in which fractional order λ ∈ (0,1) was divided into two cases, λ ∈ (0,0.5] and λ ∈ (0.5,1) , the obtained results in this article are presented in the unified form of fractional order λ ∈ (0,1) and convenient to verify. More importantly, the criteria in this article are less conservative than some existing ones. Finally, two numerical examples are given to demonstrate the validity of the proposed results.

H∞ control for singular fractional-order interval systems: The 0<α<1 case.

This paper investigates the H∞ control problems of singular fractional-order interval systems with commensurate order 0<α<1. Firstly, novel conditions for the bounded real lemma in the sense of H∞ norm for nominal singular fractional-order systems are proposed, based on which the sufficient conditions for checking the admissibility and H∞ performance of singular fractional-order interval systems are derived. Secondly, the state feedback H∞ controller synthesis for singular fractional-order interval systems is addressed and the state feedback controller is designed. Thirdly, the dynamic output feedback H∞ controller synthesis for singular fractional-order interval systems is addressed and the dynamic output feedback controller is designed. Finally, three illustrative examples are given to show the effectiveness of the proposed results.

Plasma thymidylate synthase and dihydrofolate reductase mRNA levels as potential predictive biomarkers of pemetrexed sensitivity in patients with advanced non-small cell lung cancer.

BACKGROUND: High levels of thymidylate synthase (TS) and dihydrofolate reductase (DHFR) expression in tumour tissues are an indicator of ineffective responses to pemetrexed-based chemotherapy in various tumours, including non-small cell lung cancer (NSCLC). However, tumour tissues are highly heterogeneous, so a single biopsy may not reflect genetic alterations during disease progression. This study investigated the potential use of plasma TS and DHFR mRNA levels as biomarkers for predicting sensitivity to pemetrexed-based chemotherapy. METHODS: Plasma samples were obtained from 245 patients with advanced NSCLC and 30 healthy donors. Total RNA was extracted from the plasma samples, and TS and DHFR mRNA levels were determined via real-time PCR. TS and DHFR mRNA levels between cancer patients and healthy controls were compared. The association between plasma TS and DHFR mRNA levels and tumour response to pemetrexed/cisplatin chemotherapy was analysed. RESULTS: The plasma TS and DHFR mRNA levels decreased in patients with advanced NSCLC compared with healthy controls. Moreover, plasma TS and DHFR mRNA levels negatively correlated with tumour response to pemetrexed/cisplatin chemotherapy in patients with advanced NSCLC. Overall survival time was prolonged in patients with low TS mRNA expression compared with those with high TS mRNA expression, although the difference was not statistically significant. CONCLUSIONS: Low expression levels of plasma TS and DHFR mRNA confer increased tumour sensitivity to pemetrexed/cisplatin chemotherapy in patients with advanced NSCLC. The results suggested that plasma TS and DHFR mRNA levels are promising biomarkers for choosing patients who are likely to respond and benefit the most from pemetrexed-based chemotherapy.

Observer-based H(infinity) control for networked nonlinear systems with random packet losses.

This paper investigates the observer-based H(infinity) control problem of networked nonlinear systems with global Lipschitz nonlinearities and random communication packet losses. The random packet loss is modelled as a Bernoulli distributed white sequence with a known conditional probability distribution. In the presence of random packet losses, sufficient conditions for the existence of an observer-based feedback controller are derived, such that the closed-loop networked nonlinear system is exponentially stable in the mean-square sense, and a prescribed H(infinity) disturbance-rejection-attenuation performance is also achieved. Then a linear matrix inequality (LMI) approach for designing such an observer-based H(infinity) controller is presented. Finally, a simulation example is used to demonstrate the effectiveness of the proposed method.