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As an effective global search method, genetic algorithm has obvious advantages. But it usually has problems of premature convergence and local optimum in practical application. According to this, a new algorithm with improved selection, crossover and mutation is proposed. Through the simulation experiments, the improved algorithm shows its faster convergence and better stability. It is valid which...
This paper investigates the stabilization problem for networked control systems (NCSs) with limited data rates over an additive white Gaussian noise (AWGN) channel. The notion of control with limited data rates means specifying the lower bound of data rates, above which there exists a coding and control scheme for stabilization of linear time-invariant systems. Different from the literatures, the...
This paper considers a distributed power allocation scheme for sum-rate-maximization under cognitive Gaussian multiple access channels (GMACs), where primary users and secondary users may communicate under mutual interference with the Gaussian noise. Formulating the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple distributed method to find a solution...
This paper presents an imitation mechanism and a study of its behavior in spatial grid-based configurations. The imitation mechanism replicates external signals without associating with objects, as in higher-level imitation; it is therefore a model of proto-imitation where agents imitate unconditionally the agents they happen to interact with. We study the mechanism in 2D space to understand how it...
Because there were a lot of facts that affect the intensity of coal and gas outburst, a BP neural network model for forecasting the intensity was constructed. Aimed at the shortcoming of the BP neural network, such as the slow training speed, easy to be trapped into the local optimums, and the premature convergence of genetic algorithm (GA) BP neural network, a method to design the BP neural network...
This paper introduces triangulation theory into genetic algorithm and with which, the optimization problem will be translated into a fixed point problem. An improved genetic algorithm is proposed by virtue of the concept of relative coordinates genetic coding, designs corresponding crossover and mutation operator. Through genetic algorithms to overcome the triangulation of the shortcomings of human...
This paper introduces triangulation theory into genetic algorithm and with which, the optimization problem will be translated into a fixed point problem. An improved genetic algorithm is proposed by virtue of the concept of relative coordinates genetic coding, designs corresponding crossover and mutation operator. Through genetic algorithms to overcome the triangulation of the shortcomings of human...
Based on neural network, an improvement scheme that iterative matrix replace secondary derivative has been developed by introduced quasi-Newton algorithm. Profile code based on probability has been used and comparison of window width and learning training has been completed. The experiment results indicate that the prediction for secondary structures of protein obtain a very good effect based on neural...
In order to improve some fundamental problems of the clonal selection algorithm (CSA), a novel clonal selection algorithm (NCSA) is proposed. After analyzing the mechanism of the clonal selection and proposing the antibody model, the basic character of the application problem fused into the NCSA based on rearrangements of antibody molecule coding genes. Next, we analyzed synthetically the antibody-antigen...
Density evolution (DE) is one of the most powerful analytical tools for low-density parity-check (LDPC) codes and graph codes with message passing decoding algorithms. With channel symmetry as one of its fundamental assumptions, density evolution has been widely and successfully applied to different channels, including binary erasure channels (BECs), binary symmetric channels (BSCs), binary additive...
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