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In this paper, the stability of neutral systems with mixed delays is studied. The time delays are uniformly divided into multiple segments. Then using these functionals, some new delay-dependent stability criteria are derived for the neutral systems. Numerical examples also show the results obtained in this paper improve the estimate of the delays limits for stability over some existing ones.
Feature selection, structure determination and connection weights training are three key tasks for the classification problem based on neural network. Traditional feature selection methods with neural networks neglect the fact that these three tasks are interdependent and make a joint contribution to the performance of neural network, which often results in an irrational network structure and unsatisfying...
Human capital formation and accelerating economic growth is a representative complex system which is not suitable to measure and forecast by classic linear statistical approaches. This paper proposes a novel hybrid multi-coding GA-BP-RBF model for China human capital prediction. The hybrid model combines the multi-encoding genetic algorithm (MGA) and the back propagation (BP) algorithm to form a hybrid...
As generalization ability of neural network was restricted by overfitting problem in the network’s training. Early stopping algorithm based on fuzzy clustering was put forward to solve this problem in this paper. Subtractive clustering and Fuzzy C-Means clustering (FCM) were combined to realize optimal division of training set, validation set and test set. How to realize this algorithm in backpropagation...
Neural network is widely used in pattern recognition, image processing and system control. BP neural network has its inherent deficiencies. Its convergence rate is slow. It is easy to fall into the local minimum and the structure of the neural network is hard to determine. The structure of hidden layer is determined through the experience, but it can not make accurate judgments with complex network...
A more computational spiking neural network, PTSNN, was proposed. In PTSNN, the synaptic connection weights between neurons were set to one. Network runs through modulating the PSP location in timeline of each neuron by adapting their accepted time make the network spike at the right time so that meet the requirement of classification. The weight modulating of PTSNN is determined by the error of actual...
A novel generalized predictive control algorithm with online tuning maximal output increment based on BP neural network is proposed. First,An output increment feedback predictive control algorithm is simplified by approximately computing future control increment sequence off line,then the maximal output increment is adjusted online by BP,which guarantees that output close to set-value,last,the novel...
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