In this paper, a unified framework is established to investigate both the quantized and the saturated control problems for a class of sampled-data systems under noisy sampling intervals. A random ...variable obeying the Erlang distribution is used to describe the noisy sampling intervals. In virtue of the matrix exponential, the sampled-data control system is transformed into an equivalent discrete-time stochastic system, and the aim of this paper is to design a quantized/saturated sampled-data controller such that the resulting discrete-time stochastic system is stochastically stable when the sampling error follows the Erlang distribution. In order to deal with the case of multiple control inputs, a confluent Vandermonde matrix approach is proposed in the design process. By using the Kronecker product operation and the matrix inequality techniques, the desired quantized/saturated controller gains are designed in terms of the solution to certain matrix inequalities. Finally, a simulation example is exploited to verify the effectiveness of the proposed design approach.
This study deals with the problem of the
state estimation for discrete-time memristive neural networks with time-varying delays, where the output is subject to randomly occurring denial-of-service ...attacks. The average dwell time is used to describe the attack rules, which makes the randomly occurring denial-of-service attack more universal. The main purpose of the addressed issue is to contribute with a state estimation method, so that the dynamics of the error system is exponentially mean-square stable and satisfies a prescribed
disturbance attenuation level. Sufficient conditions for the solvability of such a problem are established by employing the Lyapunov function and stochastic analysis techniques. Estimator gain is described explicitly in terms of certain linear matrix inequalities. Finally, the effectiveness of the proposed state estimation scheme is proved by a numerical example.
In this paper, a class of discrete-time delayed switched neural networks with dynamic event-triggered mechanism (DETM) and constrained bit rate is considered. In order to reduce the transmission ...frequency and alleviate the unnecessary resource loss between sensor and estimator, a DETM is proposed. The data transmission from sensor to estimator is realized through constrained bit rate channel. Therefore, in order to reflect the bandwidth allocation rules of accessible neurone nodes, a bit rate constraint model is introduced and an encoding-decoding mechanism is developed. This paper is concerned with the strategy of average dwell time (ADT) and linear matrix inequality, then sufficient conditions for the exponential ultimate boundedness of switched neural networks with DETM and constrained bit rate are proposed. Finally, an example is given to prove the effectiveness of the results.
Dear Editor, In this paper, a recursive filtering problem (RRP) is addressed for nonlinear systems over full-duplex relay (FDR) networks. A FDR is adopted to forward measurements of the sensor to the ...filter. Because of concurrently transmitting and receiving, the FDR is interfered by the signals from itself, thereby exhibiting self-interference (SI). The motivation of this letter is to design a recursive filter (RR) for the nonlinear system subject to the SI. To alleviate the SI, a SI cancellation (SIC) method is first proposed for the FDR. By analyzing the dynamics of the SI and the filtering error, an upper bound (UB) is provided for the filtering error covariance (FEC). Then, the filter gain is parameterized to minimize the UB. Finally, the performance of the proposed filtering scheme is evaluated by a numerical example.
A gaze control system for tracking Quasi-1D high-speed moving object is proposed, it can keep the object in the centre of the image within a certain range. Initially, the system structure is ...designed, and the tracking range of the system is expanded using a single saccade mirror. Then the model between the deflection angle of the saccade mirror and the pixel displacement is established. Finally, a frame-difference method based on image cropping is proposed to rapidly extract the moving object in the complex dynamic background. It feeds back the object position to the saccade mirror control system. The system adjusts the deflection angle of the saccade mirror in real time. Experimental results show that the system can satisfy the requirements of gaze control for tracking Quasi-1D high-speed moving object.
Nowadays, emerging evidence has shown adverse pregnancy outcomes, including preterm birth, preeclampsia, cesarean, and perinatal death, occurring in pregnant women after getting infected by severe ...acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the underlying mechanisms remain elusive. Thyroid hormone disturbance has been unveiled consistently in various studies. As commonly known, thyroid hormone is vital for promoting pregnancy and optimal fetal growth and development. Even mild thyroid dysfunction can cause adverse pregnancy outcomes. We explored and summarized possible mechanisms of thyroid hormone abnormality in pregnant women after coronavirus disease 2019 (COVID-19) infection and made a scientific thypothesis that adverse pregnancy outcomes can be the result of thyroid hormone disorder during COVID-19. In which case, we accentuate the importance of thyroid hormone surveillance for COVID-19-infected pregnant women.
Abstract
Background
Increasing evidence associates air pollution with thyroid dysfunction, whereas the potential relationship between exposure to ozone (O
3
) and Thyroid Nodules (TNs) is unclear.
...Methods
This retrospective cohort study investigated the association between O
3
exposure and TNs in Hunan province, enrolling 191,357 Chinese adults who lived in Hunan province from January 2009 to December 2019 and received voluntary medical examinations. Individual exposure levels to O
3
from 2010 to 2019 were measured on account of participants’ residential addresses at the district level. Associations of O
3
exposure with the risk of incidental TNs were assessed by restricted cubic splines and surveyed as odds ratios after adjusting for demographic factors.
Results
In total, 81,900 adults were newly diagnosed with TNs during the study period. Age-standardized TNs detection rate in Hunan province increased from 25.9 to 46.3% between 2010 and 2019, with the greatest annual percent change being 8.1 95% CI, 7.3–8.8. A similar trend has been found in all tumor sizes, ages, and both sexes. O
3
exposure presented a statistically significant dose-dependent positive correlation (greater than 0.036 ppm) with TNs. Similarly, long-term exposure to high levels of O
3
(1-year average O
3
concentrations exceeding 0.0417 ppm) was found positively associated with increased TSH levels.
Conclusions
High-level O
3
exposure in the long term was associated with an increase in TSH. Consequently, increased TSH was related to the increased risk of TNs. Being exposed to high-level O
3
in the long term was related to the increased detection rates of TNs in Hunan province, which could be mediated by TSH.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This paper is concerned with the recursive filtering problem for a class of uncertain systems with amplify-and-forward (AF) relays. The parameter uncertainties are described by a set of norm-bounded ...matrices. An AF relay is located between the sensor and the remote filter to forward the signal received from the sensor to the filter. A set of random variables with certain probability distribution is introduced to characterise the transmission power of the sensor and relay transmitting the measurement. By utilising the average transmission power, a robust filter is first constructed for the stochastic uncertain system. Then, an upper bound is recursively obtained for the filtering error covariance in the presence of random transmission power and parameter uncertainties. The desired gain matrix is further parameterised by minimising the obtained upper bound. Moreover, the boundness is also analysed for the filtering error. Finally, the effectiveness of the proposed filtering algorithm is demonstrated by a numerical example.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
•The stochastic nonlinearities are firstly taken into account in fusion estimation.•A new approach is proposed to transform the multi-rate system into single-rate one.•The filters designed minimize ...the upper bound of the filtering error covariance.•A new CI-based fusion estimation scheme is proposed.
This paper is concerned with the event-triggered robust fusion estimation problem for uncertain multi-rate sampled-data systems with stochastic nonlinearities and the colored measurement noises. Due to the effects of stochastic nonlinearities and parameter uncertainties, a new augmentation approach is proposed by which the multi-rate sampled-data system under consideration is transformed into the single-rate system. In order to eliminate the effect of the colored measurement noises, a measurement model with uncorrected noises is established. Based on the measurement model established, a set of local event-triggered filters is constructed and the upper bounds of the local filtering error covariances at each sampling instant are obtained. By using the Lagrange multiplier method, the local filter parameters are designed such that the upper bound obtained is minimum. For the local state estimates, a new fusion estimation scheme is proposed with the help of covariance intersection (CI) method and the consistency of the proposed CI-based fusion estimation scheme is shown. Finally, an illustrative example is presented to verify the effectiveness of the fusion estimation scheme proposed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In this paper, the event-triggered filtering problem is investigated for a class of nonlinear multi-rate systems. The nonlinearity is represented by a linear form with a norm-bounded uncertainty. In ...order to deal with the uncertainty resulting from the nonlinearities, a new augmentation approach is proposed to transform the multi-rate nonlinear system into a single-rate system. Based on the measurement outputs according to the event-triggering mechanism, an extended Kalman filter is adopted to estimate the systems state. Firstly, the upper bounds of the filtering error covariance are obtained at each sampling instant. Then, by recurring to the Lagrange multiplier method, the filter gains are obtained by minimizing the upper bound of the filtering error covariance. Finally, a simulation example is given to verify the effectiveness of the proposed filtering approach.
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