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This paper presents a bio-inspired central pattern generator (CPG) architecture for feedback control of rhythmic behavior. The CPG circuit is realized as a coupled oscillator feedback particle filter. The collective dynamics of the filter are used to approximate a posterior distribution that is used to construct the optimal control input. The architecture is illustrated with the aid of a model problem...
The multi-Bernoulli (MB) filter is a new attractive approach for multi-target filtering in the presence of clutter and detection uncertainty. However, the computational complexity grows as clutter density increases. The clutter measurements may also degrade the filtering accuracy. To eliminate the clutter measurements and reduce the computational complexity, gating technique for the Gaussian mixture...
This work studies the optimal ℓ2-ℓ∞ filter design problem for discrete-time Markovian jump repeated scalar nonlinear systems. The design focus is full- and reduced-order filters which guarantee the filtering error system to be stochastically stable with a prescribed weighted ℓ2-ℓ∞ performance. Firstly, both the mode dependent Lyapunov function approach and the positive definite diagonally dominant...
This paper considers the problem of synthesizing H2 filters subject to sparsity constraints on their structure, that is, constraints on which inputs can be used when computing the estimated value of a given output. The main result of the paper shows that, contrary to the sparse controller case, the necessary and sufficient condition for the existence of filters satisfying a given sparsity pattern...
This paper presents the development of a new numerical algorithm for statistical inference problems that require sampling from distributions which are intractable. We propose to develop our sampling algorithm based on a class of Monte Carlo methods, Approximate Bayesian Computation (ABC), which are specifically designed to deal with this type of likelihood-free inference. ABC has become a fundamental...
A new technique is developed for assessing the performance of linear and nonlinear Kalman filter based state estimators. The proposed metric will indicate the performance of these state estimators which will be primarily influenced by: (i) difference between the model dynamics and process dynamics and, (ii) various approximations of the nonlinear plant dynamics used in nonlinear Kalman filters. Currently,...
In this paper, a Moving Horizon Estimator with pre-estimation (MHE-PE) is proposed for discrete-time nonlinear systems under bounded noise. While the classical Moving Horizon Estimator (MHE) compensates for model errors by estimating the process noise sequence over the horizon via optimization, the MHE-PE does it using an auxiliary estimator. The MHE-PE is shown to require significantly less computation...
This paper presents a novel multi-frame denoising method for low light images to get a clear shot even under dark conditions. To this end, multiple short-exposure images are aligned and filtered with a temporal-spatial filter to suppress the noise. Simulation results on real low-light scenes show that the proposed method outperforms the state-of-the-art image denoising method both on processing speed...
This paper argues that the best effect to remove Gaussian noise is to use wiener filtering, and to remove salt & pepper noise to use median filtering will get a better effect. By using the correlation index, and through the original image adding noise and removing noise, it calculates the correlation index of the removal-noise image of the original image is better than traditional methods...
This paper proposes a novel active islanding fault detection method based on even harmonics injection and set-membership filtering for the distributed generation systems. Traditional active islanding detections are mainly adding disturbances to frequency or phase of the voltage reference signal. The proposed active method detects islanding fault by injecting even-order harmonics into the current reference...
The reduced-order H∞ filtering problem for nonlinear stochastic systems is studied in this paper. The considered system is subject to state dependent stochastic Gaussian white noise disturbance. By using a different design philosophy and the parallel distributed compensation technique, the fuzzy reduced-order H∞ filter design procedure is transformed into the fuzzy static output feedback controller...
Phono- and echocardiogram signals play significant role in describing heart state. In our research we derived and proposed several linear and nonlinear methods for analyzing such signals. Some of our results are described.
The paper presents a algorithm of mouth animation with adaptive speech encoding. Firstly, dialog text is encoded and filtered to the mouth code sequence according to the consistency between syllable and mouth, which is useful to determine the mouth type and reduce the frequency of jitter. Secondly, dialog speech is segmented and encoded into several audio clip encode units base on the speech energy...
Ultrasonic ranging device send out ultrasonic pulse for the measurement, the reflected acoustic wave is received by the device and changed into electrical signal by piezoelectric sensor; the distance is calculated according to the time different of sending and receiving. But there is noise in the echo acoustic wave that will affect the quality of the received signal, which will make the reading wrong...
An infrared target recognition method in complicated group backdrop based on SURF is studied in this paper. Firstly, the image is preprocessed by image enhancement method of wavelet decomposition, histogram equalization and adaptive median filtering to increase the gray differences between target and background, and then SURF is used to realize infrared target recognition. The simulation focuses on...
In today's world, one of the reason in rise of mortality among the people is brain cancer. Brain tumour is the main cause of brain cancer. A tumour can be defined as any mass caused by abnormal or uncontrolled growth of cells. This mass of tumour grows within the skull, due to which normal brain activity is hampered. Which is if not detected in earlier stage, can take away the person's life. Hence,...
This paper describes a simple and fast way to predict efficiency of DCT-based filtering of images corrupted by signal dependent noise as this often happens for hyperspectral and radar remote sensing. Such prediction allows deciding in automatic way is it worth applying denoising to a given image under condition that parameters of signal-dependent noise are known a priori or pre-estimated with appropriate...
Macromolecular structure determination using cryo-electron tomography requires large amount of subtomograms depicting the same molecule, which are averaged. In this paper, we propose a novel automatic particle picking and classification method for cryo-electron tomograms. The workflow comprises two stages: detection and classification. The detection method consists of a template-free picking procedure...
Light sheet microscopy allows rapid optical sectioning of whole chicken embryos during early development, visualizing cells through transgenic expression of a fluorescent cell membrane label. Low signal-to-noise ratios and large variability in intensity make segmentation of these images difficult, often resulting in discontinuous cell edges. We propose a multi-scale non-local means with shape prior...
This paper introduces a new perceptual speech enhancement method based on an improved Wiener filter. The classic noise reduction techniques, including the Wiener filter, introduce musical noise and distortions that remains in the enhanced speech signal, which consequently affects the perceptual appearance. Since the spectrum of speech signal is not affected uniformly by the noise it is interesting...
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