Global stability of Internet congestion controllers with heterogeneous delays

In this paper, we study the problem of designing globally stable, scalable congestion control algorithms for the Internet. Prior work has primarily used linear stability as the criterion for such a design. Global stability has been studied only for single node, single source problems. Here, we obtain conditions for a general topology network accessed by sources with heterogeneous delays. We obtain a sufficient condition for global stability in terms of the increase/decrease parameters of the congestion control algorithm and the price functions used at the links.     

On the balanced truncation of LTV systems

This note furthers results on the balanced truncation of stable linear time-varying discrete-time systems. The main result contributes better error bounds than the currently available ones in certain model reduction scenarios; this is demonstrated in an example of a four-mass translational system. Also, this note gives new finite error bounds for the balanced truncation of stable eventually periodic models.     

A continuous-time extension condition

This paper presents a continuous-time extension condition which has applications in the areas of identification and model validation of continuous-time systems. Consider two signals, specified on a finite interval. The result gives a necessary and sufficient condition for the existence of a contractive, causal, linear, time-invariant operator, mapping one signal to the other. This result is a continuous time analog of the classical Caratheodory extension theorem     

Influence of fibrinolytic factors on scar formation after lumbar discectomy. A magnetic resonance imaging follow-up study with clinical correlation performed 7 years after surgery

STUDY DESIGN: Prospective cohort study. OBJECTIVES: To assess the amount of scar tissue by viewing magnetic resonance images, and to evaluate the correlation between the amount of scar tissue and clinical outcome, surgical technique, and fibrinolytic factors. SUMMARY OF BACKGROUND DATA: The influence of fibrinolytic factors on magnetic resonance images has not been investigated previously. The relation between clinical outcome and findings on magnetic resonance imaging remains uncertain. METHODS: Magnetic resonance imaging at 0.5 Tesla was performed to produce sagittal and axial spin-echo T1-weighted images before and after contrast enhancement on 78 patients 7 years after traditional lumbar discectomy with partial or full laminectomy. Before surgery all patients had been tested for fibrinolytic factors. RESULTS: The overall clinical success rate of the surgery was 73%. No evidence of scar formation was seen in 19 patients, a small amount was seen in 36 patients, a moderate amount in 17 patients, and a large amount was observed in 6 patients. Ten patients who had undergone surgery at two disc levels and 18 who had been treated with full laminectomy exhibited more scar tissue than those patients who had undergone surgery on a single level (P = 0.033) and those who had undergone a partial laminectomy, respectively (P = 0.017). The amount of scar formation also was associated with a poor outcome (P = 0.017) and with low preoperative values of tissue plasminogen activator antigen (P = 0.003) and tissue plasminogen activity (P = 0.048) in samples collected after venous occlusion. The intensity of contrast enhancement, however, was not influenced by these or any other parameters. CONCLUSION: The amount of scar formation after lumbar discectomy seems to be related to the clinical outcome, the size of the surgical exposure, and some fibrinolytic factors.     

L1 analysis and design of sampled-data systems

The focus of this work is L₁-optimal control of sampled-data systems. A converging approximation procedure is derived to compute the L_∞-induced norm of closed-loop finite-dimensional linear time-invariant (LTI) sampled-data systems. An approximation method is developed to synthesize L₁-optimal sampled-data regulators. Finally, an example is provided that illustrates the L₁ analysis and design techniques presented     

Continuous-time control model validation using finite experimentaldata

The application of robust control theory requires models containing unknown, bounded perturbations and unknown, bounded input signals. Model validation is a means of assessing the applicability of a given model with respect to experimental data. This paper develops a theoretical framework, and a computational solution, for the model validation problem in the case where the model, including unknown perturbations and signals, is given in the continuous time domain, yet the experimental datum is a finite, sampled signal. The continuous nature of the unknown components is treated directly with a sampled data lifting theory. This gives results which are valid for any sample period and any datum length. Explicit calculation of whether sufficient data for invalidation has been obtained arises naturally in this framework. A common class of robust control models is treated and leads to a convex matrix optimization problem. A simulation example illustrates the approach     

Pressure measurements in herniated lumbar disks: association with radiologic and clinical data

Sympathetic neuronal activity is primarily responsible for the neurogenic control of cerebral autoregulation. The stimulation of sympathetic nerves causes both large arterial constriction and small vessel dilation in experimental animals. However, the role of the sympathetic nervous system in the control of cerebral hemodynamics has yet to be clarified in humans. In order to assess the effect of sympathetic activation on human cerebral hemodynamics, we performed a simultaneous transcranial Doppler (TCD) monitoring of bilateral middle cerebral arterial flow velocity in 16 healthy male volunteers (mean age 26) during well-known sympathetic activation measures such as isometric hand-grip exercise (IHE) and cold pressor test (CPT). Blood pressure was checked manually before and at each minute during tests. The mean arterial pressure (MAP) was calculated as (systolic pressure + 2 X diastolic pressure)/3. There was a significant increase in MCA flow velocities during both sympathetic activation tests. The percent increase of diastolic velocity (36% with IHE and 24% with CPT) was significantly higher than systolic velocity (21% with IHE and 9% with CPT). The pulsatility index was significantly decreased during the tests (from 0.75 to 0.58 with IHE and from 0.81 to 0.63 with CPT). These results suggest that sympathetic activation increases MCA flow velocities, related with a reduction in small vessel resistance and/or a constriction of large arteries.     

Asynchronous control for two‐dimensional hidden Markovian jump systems with partly known mode observation conditional probabilities

This study focuses on the asynchronous control problem for two‐dimensional discrete‐time hidden Markovian jump systems where the mode observation conditional probability matrix is partly known. Considering the original system modes are invisible, the observed modes emitted from an observer serve as an alternative for stability analysis and controller design where a mode observation conditional probability matrix is constructed to characterize the emission between system modes and observed modes. Specially, only partly known information of the mode observation conditional probability matrix is accessible. With the introduction of the free‐connection weighting matrices, the asymptotic mean square stability criterion is firstly derived based on Lyapunov method. This introduction provides a further degree of relaxation and less conservatism is therefore achieved. Secondly, we present synthesis conditions for asynchronous state feedback controller design given in terms of a set of interconnected linear matrix inequalities. Moreover, cluster concept based on the partitions of observed modes is adopted which helps to decrease the number of controllers and simplify the design complexity. A numerical example, regarding the cases with and without clustering of the observed modes, is presented to illustrate the effectiveness of the proposed method.     

A new approach for analysis and synthesis of time-varying systems

In this paper new techniques are developed for the analysis of linear time-varying (LTV) systems. These lead to a formally simple treatment of robust control problems for LTV systems, allowing methods more usually restricted to time invariant systems to be employed in the time-varying case. As an illustration of this methodology, the so-called H_∞ synthesis problem is solved for LTV systems     

A nonlinear functional approach to LFT model validation

Model validation provides a useful means of assessing the ability of a model to account for a specific experimental observation, and has application to modeling, identification and fault detection. In this paper, we consider a new approach to the model validation problem by deploying quadratic functionals, and more generally nonlinear functionals, to specify noise and dynamical perturbation sets. Specifically, we consider a general linear fractional transformation framework for the model structure, and use constraints involving nonlinear functional inequalities to specify model non-linearities and unknown perturbations, and characteristics of noise and disturbance signals. Sufficient conditions for invalidation of such models are provided in terms of semidefinite programming problems.