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This paper presents a digital repetitive control design on the basis of attracting law (AL). A control law, together with the disturbance compensation, can be derived by applying the AL which includes a measure of disturbance-rejection. Chattering is alleviated by a sign-function continuous approximation technique. To characterize the closed-loop performance, the steady-state error band, absolute...
The design of a novel adaptive finite-time stable control system for high-order systems with parameter uncertainties is presented. Specified dynamics with recursive structure is employed as the finite-time convergent target system, thus leading to a systematic design process for systems with arbitrary order. Estimators for unknown parameters are constructed using immersion and invariance (I&I)...
Lineage tracing, the joint segmentation and tracking of living cells as they move and divide in a sequence of light microscopy images, is a challenging task. Jug et al. [21] have proposed a mathematical abstraction of this task, the moral lineage tracing problem (MLTP), whose feasible solutions define both a segmentation of every image and a lineage forest of cells. Their branch-and-cut algorithm,...
In order to enhance the tracking performance of maneuvering target by forgetting factor RLS algorithm, an improved forgetting factor adaptive function is proposed based on cosine function. This adaptive function can adjust the forgetting factor dynamically according to the tracking error. In addition, a comprehensive predictor is designed, which dynamically selects the linear predictor or the square...
Most previous algorithms for the recognition of Action Units (AUs) were trained on a small number of sample images. This was due to the limited amount of labeled data available at the time. This meant that data-hungry deep neural networks, which have shown their potential in other computer vision problems, could not be successfully trained to detect AUs. A recent publicly available database with close...
This paper studies the mathematical modelling of Internet congestion control. Differently to previous models, which consider either the link capacity or the node processing capability as the constraint, here we take both of them into account, i.e., the aggregate flow rate on a link cannot exceed the link capacity and the aggregate flow rate at a node is limited by the node processing capability. A...
This paper studies the fully-distributed consensus problem for multi-agent systems with unknown dynamics and bounded external disturbances. The interaction topology of the multi-agent system is assumed to contain a directed spanning tree. Based on adaptive gains, we present the fully-distributed consensus protocol which can obtain consensus without using any global information. The simulation examples...
In this paper, a second-order fast terminal sliding mode control (SFTSMC) scheme with backstepping is proposed to achieve the desired tracking performance for an uncertain missile's lateral system with external disturbance. This control strategy can be applied to generate lateral control commands on missile operating in flight regimes where the effectiveness of conventional aerodynamic surfaces is...
In this paper, an adaptive adjustment method for the kernel parameter used in the kernel adaptive filters (KAFs) is proposed. The KAF is one of the linear-in-the-parameters (LIP) nonlinear filters, and is based on the kernel method used in machine learning. Typically, the Gaussian kernel function is used, but there is no effective method for automatically adjusting its parameter that influences the...
We consider the following basic problem: given an n-variate degree-d homogeneous polynomial f with real coefficients, compute a unit vector x in R{\string^}n that maximizes abs(f(x)). Besides its fundamental nature, this problem arises in diverse contexts ranging from tensor and operator norms to graph expansion to quantum information theory. The homogeneous degree-2 case is efficiently solvable as...
We develop several efficient algorithms for the classical Matrix Scaling} problem, which is used in many diverse areas, from preconditioning linear systems to approximation of the permanent. On an input n× n matrix A, this problem asks to find diagonal (scaling) matrices X and Y (if they exist), so that X A Y ε-approximates a doubly stochastic matrix, or more generally a matrix...
This paper analyzes the convergence of the rotor position tracking in signal-injection sensorless control especially for heavily saturated IPMSMs. In the analysis, it is revealed that the harmonic inductance and the operating current variation are critical factors determining the operation limit of signal-injection sensorless control. Considering this, the feasibility region of signal-injection sensorless...
Wolf pack algorithm is one of the group intelligence algorithms, which has advantages in convergence rate and objective function solving precision. But there still exists deficiency: slow convergence speed, easy to fall into the local extremum, the searching precision is not ideal and so on. In this paper, The Tent chaotic mapping strategy is used to make the population distribution even more uniform...
the optimization algorithm plays an important role in solving the complex problems, and many complex problems can be modeled as a combinatorial optimization problem. The multi-dimensional knapsack problem is a kind of typical combinatorial optimization problem. The pollination algorithm is a kind of natural heuristic algorithm proposed in recent years, which has the characteristics of few parameter...
The ADMM based linear programming (LP) technique shows interesting error correction performance when decoding binary LDPC block codes. Nonetheless, it's applicability to decode LDPC convolutional codes (LDPC-CC) has not been yet investigated. In this paper, a first flooding based formulation of the ADMM-LP for decoding LDPC-CCs is described. In addition, reduced complexity decoding schedules to lessen...
This paper proposes a low complex hardware accelerator algorithmic modification for n-dimensional (nD) FastICA methodology based on Coordinate Rotation Digital Computer (CORDIC) to attain high computation speed. The most complex and time consuming update stage and convergence check required for computation of the nth weight vector are eliminated in the proposed methodology. Using the Gram-Schmidt...
The ℓp norm-constrained proportionate normalized least-mean-square (LP-PNLMS) using the modified filtered-x structure is proposed for active noise control. It is shown that better performance is obtained for primary and secondary paths having a wide range of sparseness levels when compared with competing sparsity-inducing algorithms at a price of moderate complexity increase.
In this paper the reaching law approach to designing sliding mode controllers is used. In particular, the case of switching variable of relative degree r > 1 is considered. It is demonstrated, that the use of such a variable allows more freedom in designing the controller and can result in reducing the maximum absolute value of the control signal without compromising the robustness with respect...
Reaching law approach is a straightforward method of ensuring the desired dynamic response of a variable structure system. In our paper, this method is used to design a new non-switching type discrete time sliding mode control strategy. The strategy is shown to ensure a finite time reaching phase, stability of the sliding motion and bounded convergence rate of the sliding variable to the vicinity...
We show that the KLS constant for n-dimensional isotropic logconcavemeasures is O(n^{1/4}), improving on the current best bound ofO(n^{1/3}√{\log n}). As corollaries we obtain the same improvedbound on the thin-shell estimate, Poincar\e constant and Lipschitzconcentration constant and an alternative proof of this bound forthe isotropic constant; it also follows that the ball walk for samplingfrom...
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