The nonlinearity measurement of charge-coupled device array spectrometer using colorful LED

A nonlinearity measurement of the charge-coupled device(CCD) array spectrometer using flux addition and comparison method is described. The light with various colors from the colorful light emitting diode(LED) light source is applied to measure the nonlinearity of the spectrometer at different wavelengths, respectively. An high-end CCD array spectrometer is tested. For colorful LED light sources, the nonlinearity factors of the CCD array spectrometer(absolute value) are as follows: k<0.8% for white light, k <1.1% for red light, k <2.2% for green light and k<4.7% for blue light. By using those quasi-monochromatic light sources, it is shown that the nonlinearity depends on the wavelength. It is important to be wariness about the spectral nonlinearity and related uncertainty evaluation when the narrow-band light source is tested.

Active Disturbance Rejection Control for Uncertain Nonlinear Systems With Sporadic Measurements

This paper deals with the problem of active disturbance rejection control(ADRC)design for a class of uncertain nonlinear systems with sporadic measurements.A novel extended state observer(ESO)is designed in a cascade form consisting of a continuous time estimator,a continuous observation error predictor,and a reset compensator.The proposed ESO estimates not only the system state but also the total uncertainty,which may include the effects of the external perturbation,the parametric uncertainty,and the unknown nonlinear dynamics.Such a reset compensator,whose state is reset to zero whenever a new measurement arrives,is used to calibrate the predictor.Due to the cascade structure,the resulting error dynamics system is presented in a non-hybrid form,and accordingly,analyzed in a general sampled-data system framework.Based on the output of the ESO,a continuous ADRC law is then developed.The convergence of the resulting closed-loop system is proved under given conditions.Two numerical simulations demonstrate the effectiveness of the proposed control method.

The chaotification of discrete Hopfield neural networks via impulsive control

The chaotification of discrete Hopfield neural networks is studied with impulsive control techniques. No matter whether the original systems are stable or not, chaotilication theorems for discrete Hopfield neural networks are derived, respectively. Finally, the effectiveness of the theoretical results is illustrated by some numerical examples.

Information Feedback Strategies in a Signal Controlled Network with Overlapped Routes

We investigate the effects of four different information feedback strategies on the dynamics of traffic, travelers＇ route choice and the resultant system performance in a signal controlled network with overlapped routes. Simulation results given by the cellular automaton model show that the system purpose-based mean velocity feedback strategy and the congestion coefficient feedback strategy have more advantages in improving network utilization efficiency and reducing travelers＇ travel times. The travel time feedback strategy and the individual purposed-based mean velocity feedback strategy behave slightly better to ensure user equity.

INITIAL-OBLIQUE DERIVATIVE PROBLEMS FOR NONLINEAR PARABOLIC SYSTEMS WITH MEASURABLE COEFFICIENTS

This paper deals with some initial-oblique derivative boundary value problems for nonlinear nondivergent parabolic systems of several second order equations with measurable coefficients in multiply connected domains. Firstly, a priori estimates of solutions for the initial-boundary value problems are given, and then by using the above estimates of solutions and the Leray-Schauder theorem, the existence and uniqueness of solutions for the problems are proved.

Chaos Control and Synchronization of Cellular Neural Network with Delays Based on OPNCL Control

The problem of chaos control and complete synchronization of cellular neural network with delays is studied. Based on the open plus nonlinear closed loop （OPNCL） method, the control scheme and synchronization scheme are designed. Both the schemes can achieve the chaos control and complete synchronization of chaotic neural network respectively, and their validity is further verified by numerical simulation experiments.

APPLICATIONS OF NONLINEAR MEASURE ABOUT l^2-NORM TO SYNCHRONIZATION ANALYSIS OF COMPLEX NETWORKS VIA THE GENERAL INTERMITTENT CONTROL

Based on the nonlinear measure about /-norm,a novel and effective approach is applied to estimate the scope of state vectors of dynamic systems.By the general intermittent control,some simple yet generic criteria are derived ensuring the exponential stability of dynamic systems.The numerical simulations,whose theoretical results are applied to robust synchronization of complex networks,demonstrate the effectiveness and feasibility of the proposed technique.

Applying nonlinear filtering in reverberation time measurement under strong background noise

Nonlinear filtering of impulse response obtained by M-sequence correlation method under strong background noise is presented. The research shows that the new method works very efficiently without the need to cut off impulse response data. Even if the ratio of signal to noise is below -15 dB, the same decay curve ranges can still be obtained as when S/N > 40 dB