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This paper investigates the exponential synchronization problem of stochastic complex dynamical networks with impulsive perturbations and Markovian switching. The complex dynamical networks consists of κ modes and the networks switch from one mode to another according to a Markovian chain with known transition probability. Basing on the Lyapunov functional method and stochastic analysis, by employing...
This paper is concerned with the design problem of multi-sensor optimal H∞ fusion controller for a class of discrete-time systems with missing measurements. Based on Lyapunov theory and linear matrix inequality technology, the centralized and distributed fusion controllers are designed, respectively such that, for all possible missing measurements, the closed-loop systems are asymptotically stable...
This paper studies the synchronization problem of multi-agent systems with nonlinear dynamics in mean square. It is supposed that the measurement of relative-state is disturbed. For the nonlinear multi-agent systems, we show that the conventional consensus protocols are robust against the measurement noises which are dependent to the relative-state. Simulations are provided to demonstrate the theoretical...
For the multisensor single channel autoregressive moving average (ARMA) signal with a white measurement noise and autoregressive (AR) colored measurement noises as common disturbance noises, when the model parameters and noise statistics are partially unknown, a self-tuning weighted fusion Kalman filter is presented based on classical Kalman filter method. The local estimates are obtained by applying...
This paper highlights the sub-band average energy variance (SBAEV) approach to perform the endpoint detection process, which involves the segmentation of speech signals from non-speech signals. The SBAEV models have been proposed to perform endpoint detections of isolated digit utterances spoken in the Language. Experiment results obtained from this method are acoustically verified, visually checked...
A non-destructive detection system based on machine vision was designed for identifying the fertility of eggs prior to virus cultivation. Specific imaging system and detection algorithm were presented. A method based on smallest univalve segment assimilating nucleus was introduced to distinguish the high-brightness speckle noise pixels in egg images since the high transmittance of holes in eggshell...
This paper presents slosh control within a container which represents an underactuated system. The dynamics of the system is highly coupled and non-linear. The major difficulty is in slosh state measurement. Hence an Output-feedback control is proposed. The non-linear sliding surface is a function of only measurable output variables. A robust exact Levant differentiator is designed for estimating...
In this paper, we study the optimal tracking performance problem of continuous-time linear multi-input multi-output (MIMO) networked control systems. The unstable and non-minimum phase systems is considered. The output feedback path is subject to quantization noise, additive white Gaussian noise and bandwidth constraints, and encoding and decoding are considered. The reference input is a random signal...
In order to improve the performance of gyroscopes, the random drift error of a micro electro mechanical system (MEMS) gyro was analyzed and modeled. The noise feature of MEMS gyro is analyzed based on the AR model. By introducing a fading factor of Strong Tracking Filter (STF), the Sage-Husa adaptive Kalman filter reduced the effect of the error of model and noise statistical characteristics. The...
Average neighborhood margin maximization (ANMM) is a feature extraction method to make homogeneous points collect as near as possible and heterogeneous points disperse as far away as possible. To enhance the anti-noise ability of ANMM, correntropy based average neighborhood margin maximization (CANMM) is proposed in this paper. This method utilizes correntropy to substitute the Euclidean distance...
This paper considers the problem of global output feedback control for a class of nonlinear systems with inverse dynamics. The main contribution of paper is that: For the inverse dynamics with uncertain ISS/iISS supply rates, we construct a reduced-order observer-based output feedback controller, which drives the output of system to zero and maintain other closed-loop signals bounded. Finally, a simulation...
This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency characteristic of the fractional derivative for extracting more structure feature details. A thresholding...
The ultra-low orbit satellites generally orbit at an altitude about 200km, and have better performance of observing the Earth and receiving information while using the same observation instrument, thus have good economic benefits and broad application prospects. However, the aerodynamic forces and moments interference to the ultra-low-orbit satellites are dozens of orders of magnitude higher than...
A new method for removal of wide density salt and pepper noise in image is proposed. Every pixel in a noise corrupted image is classified to which it is a noise pixel or noise-free pixel. A noise pixel should be modified by a filter. On the contrary, noise-free pixel is kept unchanged. If noise-free pixel is detected as noise pixel wrongly, the restored image will be blurred. The difference between...
Misalignment angles estimation of strapdown inertial navigation system (INS) using global positioning system (GPS) data is highly affected by measurement noises, especially with noises displaying time varying statistical properties. Hence, adaptive filtering approach is recommended for the purpose of improving the accuracy of in-motion alignment. In this paper, a simplified form of Celso's adaptive...
To improve Maneuver Target Tracking Algorithm, The multi-model intelligent input estimating method based on fuzzy logic is proposed. A fuzzy inference system is constructed with the input of the residual of observation and the residual variation. Then we could get the real-time estimate of the maneuver input of the model according to the output of the system. The algorithm is optimized by the parameter...
The iterative learning control (ILC) is constructed for the discrete-time stochastic systems with random measurement losses modeled by a stochastic sequence. A simple P-type update law is used and the almost sure convergence is strictly proved for both linear case and nonlinear case based on stochastic approximation. Illustrative examples show the effectiveness of the proposed approach.
Focusing on the problem of the input and output data both contain measurement noise in linear time invariant system, this paper proposes that utilizing Tikhonov regularization of total least squares to solve the ill-poseness in process of adaptive dynamic programming. By applying the presented algorithm, the designed controller is obtained through the input and output data of the system, i.e. the...
Image super resolution (SR) reconstruction technique is receiving increasing attention from the image processing community, and it has been widely used in many applications such as remote sensing image, medical image, video surveillance and high definition television. The essential of image SR reconstruction technique is how to produce a clearly high resolution (HR) image from the information of one...
The Probability Hypothesis Density (PHD) filter is a more tractable alternative to the Random Finite Set (RFS) based optimal multitarget Bayes recursion. In this paper, a matrix reformulation of the Gaussian Mixture PHD (GM-PHD) filter is introduced. Thus a new multisensor GM-PHD filter is constructed based on the matrix reformulation. Simulation results show it can be used in some applications when...
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