a sigmoid function is necessary for creation a chaotic neural network (cnn). in this paper, a new function for cnn is proposed that it can increase the speed of convergence. in the proposed method, we use a novel signal for controlling chaos. both the theory analysis and computer simulation results show that the performance of cnn can be improved remarkably by using our method. by means of this...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

We have studied the chaos control in chaotic neural network by limiting the phase space at varying time interval. It provides a controlled output patterns with different temporal periods depending upon the control parameters. The chaotic neural network constructed with chaotic neurons exhibits very rich dynamic behavior with a non–periodic associative memory. In the chaotic neural network, it i...

In this paper, the chaotic time series RBF neural network model was designed. A prediction method for underwater acoustic chaotic signal based on RBF neural network is proposed in this paper according to the characteristics of chaotic signal with the short-term prediction. Typical Henon chaotic signal and the actual underwater acoustic chaotic signal are respectively predicted by the RBF neural...

This novel chaotic neural network bases on the Chen's transiently chaotic neural network. It is proposed by introducing radial basis function as disturbance item into the inside state. Analyze the dynamics behavior of the single chaotic neuron and the chaotic search capability of the network. Research the capability of the novel network for resisting the disturbance. This chaotic neural network...

The chaotic neural network constructed with chaotic neuron shows the associative memory function, but its memory searching process cannot be stabilized in a stored state because of the chaotic motion of the network. In this paper, a pinning control method focused on the chaotic neural network is proposed. The computer simulation proves that the chaos in the chaotic neural network can be control...

this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

In this paper, we propose a new implementation of chaotic generator using artificial neural network. Neural network can act as an efficient source of perturbation in the chaotic generator which increases the cycle’s length, and thus avoid the dynamical degradation due to the used finite dimensional space. On the other hand, the use of neural network enlarges the key space of the chaotic generat...