Stability Analysis for Delayed Neural Networks via a Generalized Reciprocally Convex Inequality.

This article deals with the stability of neural networks (NNs) with time-varying delay. First, a generalized reciprocally convex inequality (RCI) is presented, providing a tight bound for reciprocally convex combinations. This inequality includes some existing ones as special case. Second, in order to cater for the use of the generalized RCI, a novel Lyapunov-Krasovskii functional (LKF) is constructed, which includes a generalized delay-product term. Third, based on the generalized RCI and the novel LKF, several stability criteria for the delayed NNs under study are put forward. Finally, two numerical examples are given to illustrate the effectiveness and advantages of the proposed stability criteria.

Delay-Dependent Stability Analysis of Load Frequency Control Systems With Electric Vehicles.

This article investigates the problem of delay-dependent stability for the one-area load frequency control (LFC) system with electric vehicles (EVs). Two closed-loop models of the LFC system with EVs are proposed, including the model based on the model reconstructed technique and the model with uncertain parameters that considers state of charge. By employing the Lyapunov-Krasovskii functional method, two delay-dependent stability criteria are presented for the systems under study such that a more accurate admissible delay upper bound (ADUB) can be obtained. Case studies are finally carried out to disclose the interrelationship between the ADUB, PI controller gains, and other parameters of the EVs.

A New Looped Functional to Synchronize Neural Networks With Sampled-Data Control.

This article deals with the problem of sampled-data-based synchronization of neural networks with and without considering time delay. A novel looped functional is introduced in the construction of Lyapunov functional, which adequately utilizes the state information of e(tk) , e(t) , e(tk+1) , e(tk-τc) , e(t-τc) , and e(tk+1-τc) . Then, by using this functional and employing a generalized free-matrix-based integral inequality (GFMBII), several sufficient conditions are derived to ensure that the slave system is synchronous with the master system. Also, the sampled-data controller can be obtained by using the linear matrix inequality (LMI) technique. Finally, two numerical examples are illustrated to show the validity and advantages of the proposed method.

Dissipativity Analysis for Neural Networks With Time-Varying Delays via a Delay-Product-Type Lyapunov Functional Approach.

This article is concerned with the problem of dissipativity and stability analysis for a class of neural networks (NNs) with time-varying delays. First, a new augmented Lyapunov-Krasovskii functional (LKF), including some delay-product-type terms, is proposed, in which the information on time-varying delay and system states is taken into full consideration. Second, by employing a generalized free-matrix-based inequality and its simplified version to estimate the derivative of the proposed LKF, some improved delay-dependent conditions are derived to ensure that the considered NNs are strictly ( Q , S , R )- γ -dissipative. Furthermore, the obtained results are applied to passivity and stability analysis of delayed NNs. Finally, two numerical examples and a real-world problem in the quadruple tank process are carried out to illustrate the effectiveness of the proposed method.

Event-triggered H∞ filter design for sampled-data systems with quantization.

This study verifies the H∞ filter design for sampled-data systems with quantization and event-triggered schemes. Firstly, an event-triggered mechanism is presented to detect the release of the necessary sampled-data packet, which significantly reduces the limited network resources compared with the conventional time-triggered mechanism. Secondly, by considering the impact of quantization on the sampled-data system and using the time interval analysis approach, a new sampled-data filtering error model is presented. Then, the Lyapunov-Krasovskii functional (LKF) approach is utilized to derive the required conditions to ensure the asymptotical stability and attain the prescribed H∞ performance for the mentioned system by solving a group of linear matrix inequality (LMIs). Consequently, the corresponding event-triggered and H∞ parameters are co-designed. Finally, the efficiency and the advantage of the presented approach are demonstrated via a mass-spring system example.

Effect of uric-acid-lowering therapy on progression of chronic kidney disease: a meta-analysis.

The efficacy and safety of uric-acid-lowering therapy (UALT) on slowing the progression of chronic kidney disease (CKD) accompanied by hyperuricemia were assessed. We searched Cochrane Library, PubMed, EMbase, CNKI, Wanfang and Vip databases up to November 15, 2012 for randomized controlled trials (RCTs) which compared the effect of UALT to control therapy in hyperuricemic patients secondary to CKD, and then performed quality evaluation and meta-analysis on the included studies. Seven RCTs involving 451 cases were included. UALT delayed the increase of serum creatinine (MD=-62.55 µmol/L, 95% CI: -98.10 to -26.99) and blood urea nitrogen (MD= -6.15 mmol/L, 95% CI: -8.17 to -4.13) as well as the decrease of glomerular filtration rate [MD=5.65 mL/(min·1.73 m2), 95% CI: 1.88 to 9.41], decreased systolic blood pressure (SBP) (MD= -6.08 mmHg, 95% CI: -11.67 to -0.49), and reduced the risk of the renal disease progression (RR=0.30, 95% CI: 0.19 to 0.46). However, there was no statistically significant difference in 24-h urinary protein quantity and diastolic blood pressure (P>0.05). We identified that UALT could delay the progression of CKD with secondary hyperuricemia. And this also indirectly proved that hyperuricemia was a risk factor for the CKD progression.

Improved stability criteria of static recurrent neural networks with a time-varying delay.

This paper investigates the stability of static recurrent neural networks (SRNNs) with a time-varying delay. Based on the complete delay-decomposing approach and quadratic separation framework, a novel Lyapunov-Krasovskii functional is constructed. By employing a reciprocally convex technique to consider the relationship between the time-varying delay and its varying interval, some improved delay-dependent stability conditions are presented in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the merits and the effectiveness of the proposed methods.

Improved stabilization method for Lurie networked control systems.

The problem of stabilization of Lurie networked control systems (NCSs) is investigated in this paper. The network-induced delays in NCSs are assumed to be time-varying and bounded. By utilizing a reciprocally convex technique to consider the relationship between the network-induced delay and its varying interval, a new absolute stability condition is derived in terms of linear matrix inequalities (LMIs). Based on the obtained condition, an improved cone complementary linearisation (CCL) iteration algorithm is presented to design a state feedback controller. The effectiveness of the proposed method is verified by a numerical example.

Improved conditions for passivity of neural networks with a time-varying delay.

The passivity of neural networks with a time-varying delay and norm-bounded parameter uncertainties is investigated in this paper. A complete delay-decomposing approach is employed to construct a Lyapunov-Krasovskii functional. Then, by utilizing a segmentation technique to consider the time-varying delay and its derivative and introducing some free-weighting matrices to express the relationship between the time-varying delay and its varying interval, some improved passivity criteria are derived. Finally, two numerical examples are given to show the effectiveness and the merits of the proposed method.

Prevention of infection in immunosuppressive patients with autoimmune nephrosis by using an immunostimulating bacterial lysate Broncho-vaxom.

UNLABELLED: The utilization of immunosuppressive agents presents patients with autoimmune nephrosis at a high risk of infection. The present trial was to investigate the efficacy and safety of Broncho-Vaxom on preventing infection in immunosuppressive patients with autoimmune nephrosis. METHODS: 40 patients with autoimmune nephrosis were randomly divided into two groups. The control group (20 cases) routinely received corticosteroid and (or) immunosuppressive therapy, while the treatment group (20 cases) received a capsule containing 7 mg Broncho-Vaxom daily for the first 10 d of each month for 3 consecutive months on the basis of conventional corticosteroid and (or) immunosuppressive therapy. The condition of infection and blood lymphocyte were assessed. RESULTS: 4 patients in the treatment group and 5 patients in the control group were lost during the follow-up period. 25% of patients in the treatment group and 40% of patients in the control group suffered infection. There was no difference in the incidence of infection between the two groups (p > 0.05), while Broncho-Vaxom treated patients suffered a shorter infection period and of which fewer patients need to receive antibiotics therapy (p < 0.05). After the treatment with Broncho-Vaxom, the total number of blood T lymphocyte, proportion of CD4 (+) T lymphocyte, CD4 (+) /CD8 (+) reduced less and the serum IgG rose more obviously (p < 0.05), but the blood lymphocyte, B lymphocyte, CD8 (+) T lymphocyte, IgA and IgM have no differences between the two groups (p > 0.05). CONCLUSION: Broncho-Vaxom might be a good choice for preventing the respiratory infection in nephrosis, especially in the patients under the therapy of immunosuppressive agents.

Complete delay-decomposing approach to asymptotic stability for neural networks with time-varying delays.

This paper is concerned with the problem of stability of neural networks with time-varying delays. A novel Lyapunov-Krasovskii functional decomposing the delays in all integral terms is proposed. By exploiting all possible information and considering independent upper bounds of the delay derivative in various delay intervals, some new generalized delay-dependent stability criteria are established, which are different from the existing ones and improve upon previous results. Numerical examples are finally given to demonstrate the effectiveness and the merits of the proposed method.