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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 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.
We study streaming principal component analysis (PCA), that is to find, in O(dk) space, the top k eigenvectors of a d× d hidden matrix \bold \Sigma with online vectors drawn from covariance matrix \bold \Sigma.We provide global convergence for Ojas algorithm which is popularly used in practice but lacks theoretical understanding for k≈1. We also provide a modified variant \mathsf{Oja}^{++}...
Iterative learning control (ILC) is a simple technique devised for repetitive systems. In this work, an inter-sample ILC algorithm is proposed for the speed control problem of an induction motor. The proposed algorithm is mathematically analyzed and validated using a real-time experiment. Its performance is observed to be better than that of PI based Field Oriented Control (FOC) regarding convergence...
In several previous works, the two-channel adaptive filtering algorithms have been proposed and combined with forward-and-backward blind source separation structures for acoustic noise reduction and speech enhancement. Recently in [1], we have proposed a new two-channel subband forward algorithm (2CSF) for acoustic noise reduction. The main drawback of this algorithm is its poor performance in steady...
Cuckoo Search is a recent nature-inspired metaheuristic algorithm, inspired by the cuckoo birds' aggressive strategy to breeding. The Cuckoo Search algorithm iteratively uses a Lévy flight random walk to explore a search space. The Lévy flight mechanism takes sudden turns of 90 degrees and consequently the Cuckoo's Search strategy does not carefully search around the cuckoos' nest, and hence it suffers...
Underwater acoustic (UWA) channel is a complex time-space- and frequency-variant channel, which is one of the most difficult wireless communication channels so far. Coherent communication has become a hotspot in high speed underwater acoustic communication. To achieve the low bit error rate and high data transmission rate, the channel equalization technique must be introduced for coherent underwater...
Classical differential evolution (DE) is a good optimization algorithm with simple structure, easy operation and strong global search ability. Yet it is also inadequate. In this paper, a novel improved differential evolution called mean guiding differential evolution (MGDE) has been presented. By using difference information between amean individual and the best individual of previous generation to...
This paper has as a start point the metaheuristic Particle Swarm Optimization (PSO), which has very good abilities to solve many types of optimization problems. As a main contribution, this work proposes an intelligent algorithm derived from PSO. This algorithm has two main characteristics. The first one consists in the use of an improved version of PSO, namely Hybrid Topology Particle Swarm Optimization...
The traditional iterative closest point (ICP) algorithm could register two points sets well, but it is easily affected by local dissimilar. To deal with this problem, this paper proposes an isotropic scaling ICP algorithm with corner point constraint. First, an objective function is proposed under the guidance of the corner points, as the corner points can preserve the similar of the whole shapes...
This study rewrote a fractional-order particle swarm optimizer algorithmic equation and used an improved uniform design method (IUDM) to find the best combination for parameters of FPSO. Compared to PSO, FPSO makes a high convergence rate. In the improved FPSO, there are 4 parameters to influence effectiveness. Uniform design is an experimental method and suitable for multiple parameters and multiple...
Dual methods can handle easily complicated constraints in convex problems, but they have typically slow (sublinear) convergence rate in an average primal point, even when the original problem has smooth strongly convex objective function. Primal projected gradient-based methods achieve linear convergence for constrained, smooth and strongly convex optimization, but it is difficult to implement them,...
Quantum-behaved particle swarm optimization (QPSO) is a novel variant of particle swarm optimization (PSO), inspired by quantum mechanics. Compared with traditional PSO, the QPSO algorithm guarantees global convergence and has less number of controlling parameters. However, QPSO is likely to get trapped into a local optimum because of using a single search strategy. This paper proposes a cooperative...
The dynamic characteristics of a hydraulic turbine governing system is determined by the parameters of the hydraulic turbine governor. There are several drawbacks of the conventional particle swarm algorithm in parameter optimization, such as low speed of convergence, low accuracy and being inclined to result in partial optimization during the process of optimization. This paper introduced concave...
Least-squares temporal difference learning (LSTD) has been used mainly for improving the data efficiency of the critic in actor-critic (AC). However, convergence analysis of the resulted algorithms is difficult when policy is changing. In this paper, a new AC method is proposed based on LSTD under discount criterion. The method comprises two components as the contribution: (1) LSTD works in an on-policy...
In this paper, we consider the privacy preserving problem in an agreement network under interception attacks. First, we introduce a consensus protocol with privacy preserving, where each node hides their initial states into a set of random sequences, and then injects the sequences into the process of consensus. Second, we assume that an attacker with limited power can intercept the data transmitted...
Correntropy induced metric (CIM) criterion has been extensively studied for measuring the sparsity property of the in-nature sparse signals. In this paper, a CIM constrained l2–lp (CIM-L2LP) adaptive filtering algorithm is proposed and its convergence analysis is given in detail. By using a CIM penalty, the CIM-L2LP algorithm achieves improved convergence speed while it maintains a lower steady state...
The conventional infinite-length extrinsic information transfer (EXIT) charts would not be accurate for short-length coded systems, because short-length coded sequences do not possess ergodicity as infinite-or very-long length coded sequences. In this paper, we concern with the finite-length EXIT analysis, which is developed for protograph low-density parity-check (PG-LDPC) codes over underwater acoustic...
This paper presents three implementation algorithms of compound elements pseudo-transient analysis to find DC solutions for nonlinear LSI circuits. In former researches, CEPTA was implemented in SPICE-like simulator with the merits that the size of Jacobian matrix is not expanded during the calculation. While the inserted pseudo parts are converted to some certain equivalent circuits, the conventional...
Finite-time consensus of heterogeneous multi-agent system (MAS) with external disturbances is investigated in this paper. Distributed control algorithm is designed for the agents described by leaderless MAS. It can be shown that the state errors of any two agents reach a region in finite time with external disturbances by using Lyapunov stability analysis and algebraic graph theory. At last, one example...
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