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A novel adaptive nonlinear controller is presented for nonlinear active noise control systems, which is expanded by memory function mapping on the basis of a single neuron structure, and a generalized filtered-X gradient descent algorithm is developed to attenuate the nonlinear, non-Gaussian noises, which defines the weighted sum of Renyi's quadratic error entropy and the mean square error as the...
A particle swarm optimization algorithm with partial mutation strategy (PMPSO) is developed. During the searching process, only premature convergence particles are mutated to escape from local optimum, and they are no more mutated in next several generations in order to search efficiently in other areas; other non-premature particles go on their evolutions normally. Several parameters of the PMPSO...
According to the framework of Dempster-Shafer evidence theory, information fusion relies on the use of a combination rule allowing the belief functions for the different propositions to be combined. Dempster's rule of combination is a basic rule of combination. However, Dempster's combination operator is poor in the management of the conflict among the various information sources at the normalization...
In this paper, a modified Differential Evolution (MDE) is proposed for solving the Integer Programming problems. In order to increase the probability of each parent to generate a better offspring, each solution is allowed to generate more than one offspring through six different mutation operators. A migration operator is designed to overcome premature convergence of DE. In practical applications,...
In this note, we shall derive the functional equation for the Hurwitz zeta-function ??(s,u) from that for the Riemann zeta-function ??(s), on using an integral expression for ??(s,u) which in turn depends on the functional equation for ??(s).
The Elitism, which is the mechanism to incorporate external useful solutions in MOEA, is popular technology. One of the focus of research about elitism is how to maintain and select the global guide in order to keep the results of algorithm convergence and diversity. In this paper, a novel method to maintain elitism archive and select global guide is proposed, which divide the non-dominated solutions...
Feature extraction of event related potential (ERP) plays an important role in both fundamental and clinical research for cerebral neurophysiology. ICA is a method for separating blind signals based on signal statistic characteristics. In this paper, the fundamental, discrimination condition and practical algorithm of Independent Component Analysis are discussed. Then, a fast Independent Component...
The Middleton class A interference model is a statistical-physical and parametric model for man-made and natural electromagnetic (EM) interference. In this paper, the efficient estimation of the Class A model parameters based on least square gradient method is derived. The considered estimator converges fast and low-complexity with performance approaching theoretical optima for large data samples...
In this paper, we propose a Q-learning with continuous action policy and extend this algorithm to a multi-agent system. We examine this algorithm in a task that there are two robots taking action independently but connected with a straight bar. The robots must cooperate to move to the goal and avoid the obstacles in the environment. Conventional Q-learning needs a pre-defined and discrete state space...
This paper describes a step-size parameter adaptation technique of multi-channel semi-blind independent component analysis (MCSB-ICA) for a ??barge-in-able?? robot audition system. By ??barge-in??, we mean that the user can speak simultaneously when the robot is speaking.We focused on MCSB-ICA to achieve such an audition system because it can separate a user's and a robot's speech under reverberant...
In this contribution, we propose a new technique for collaborative sensing based on the analysis of the normalized (by the trace) largest eigenvalues of the sample covariance matrix. Assuming that several base stations are cooperating and without the knowledge of the noise variance, the test is able to determine the presence of mobile users in a network when only few samples are available. Unlike...
Particle swarm optimization (PSO) is known to suffer from stagnation once particles have prematurely converged to any particular region of the search space. The proposed regrouping PSO (RegPSO) avoids the stagnation problem by automatically triggering swarm regrouping when premature convergence is detected. This mechanism liberates particles from sub-optimal solutions and enables continued progress...
Biogeography-based optimization (BBO) is an evolutionary algorithm that is based on the science of biogeography. Biogeography is the study of the geographical distribution of organisms. In BBO, problem solutions are represented as islands, and the sharing of features between solutions is represented as migration between islands. This paper develops a Markov analysis of BBO, including the option of...
Hypervolume indicator is a commonly accepted quality measure to assess the set of non-dominated solutions obtained by an evolutionary multiobjective optimization algorithm. Recently, an emerging trend in the design of evolutionary multiobjective optimization algorithms is to directly optimize a quality indicator. In this paper, we propose a hypervolume-based evolutionary algorithm for multiobjective...
In this paper we have studied the Runge-Kutta multiresolution time-domain (RK-MRTD) scheme, in which the electromagnetic fields are expanded by the Coifman scaling functions as basis function. We have analyzed the convergence of the Runge-Kutta MRTD scheme based on the Coifman scaling functions by the theoretical solution predictions on the convergence and the numerical simulations. Because of the...
The limit theorems is one of the central questions for studying in the International Probability theory. In this paper, some strong limit theorems for Markov chains of continuous state space on a non-homogeneous tree were obtained by constructing a non-negative martingale.
This paper studies the characteristic of NGA (Natural Gradient Algorithm), and propose a set of improved natural gradient blind separation algorithm by applying data preprocessing and constructing learning factor and nonlinear function. For data preprocessing we use de-mean and whitening method to preprocess original data to reduce the amount of computation during iteration in BSS (blind source separation)...
In this note we shall derive Hermite’s formula for the Hurwitz zeta-function from the functional equation for the Riemann zeta-function and derive Binet’s second expression for the gamma function form Hermite’s formula, thus deriving properties of the gamma function from the zeta-function.
In wireless networks, communication links may be subject to random fatal attacks: for example, sensor networks under sudden power losses or cognitive radio networks with unpredictable primary user spectrum occupancy. Under such circumstances, it is critical to quantify how fast and reliably information can be collected over attacked links. In our previous work, we studied such channels by considering...
Particle swarm optimization (PSO) algorithms have gained increasing interest for dealing with continuous optimization problems in recent years. Often such problems involve boundary constraints. In this case, one has to cope with the situation that particles may leave the feasible search space. To deal with such situations different bound handling methods have been proposed in the literature and it...
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