Controlling chaos in a chaotic neural network
نویسندگان
چکیده
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 controlled with this method and the states of the network can converge in one of its stored patterns if the control strength and the pinning density are chosen suitable. It is found that in general the threshold of the control strength of a controlled network is smaller at higher pinned density and the chaos of the chaotic neural network can be controlled more easily if the pinning control is added to the variant neurons between the initial pattern and the target pattern.
منابع مشابه
AN IMPROVED CONTROLLED CHAOTIC NEURAL NETWORK FOR PATTERN RECOGNITION
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...
متن کاملDesign and Simulation of Adaptive Neuro Fuzzy Inference Based Controller for Chaotic Lorenz System
Chaos is a nonlinear behavior that shows chaotic and irregular responses to internal and external stimuli in dynamic systems. This behavior usually appears in systems that are highly sensitive to initial condition. In these systems, stabilization is a highly considerable tool for eliminating aberrant behaviors. In this paper, the problem of stabilization and tracking the chaos are investigated....
متن کاملHybrid Control to Approach Chaos Synchronization of Uncertain DUFFING Oscillator Systems with External Disturbance
This paper proposes a hybrid control scheme for the synchronization of two chaotic Duffing oscillator system, subject to uncertainties and external disturbances. The novelty of this scheme is that the Linear Quadratic Regulation (LQR) control, Sliding Mode (SM) control and Gaussian Radial basis Function Neural Network (GRBFNN) control are combined to chaos synchronization with respect to extern...
متن کاملChaotic Test and Non-Linearity of Abnormal Stock Returns: Selecting an Optimal Chaos Model in Explaining Abnormal Stock Returns around the Release Date of Annual Financial Statements
For many investors, it is important to predict the future trend of abnormal stock returns. Thus, in this research, the abnormal stock returns of the listed companies in Tehran Stock Exchange were tested since 2008- 2017 using three hypotheses. The first and second hypotheses examined the non-linearity and non-randomness of the abnormal stock returns ′ trend around the release date of annual fin...
متن کاملNeural Predictive Control of Unknown Chaotic Systems
Abstract. In this work, a neural networks is developed for modelling and controlling a chaotic system based on measured input-output data pairs. In the chaos modelling phase, a neural network is trained on the unknown system. Then, a predictive control mechanism has been implemented with the neural networks to reach the close neighborhood of the chosen unstable fixed point embedded in the chaot...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Neural networks : the official journal of the International Neural Network Society
دوره 16 8 شماره
صفحات -
تاریخ انتشار 2003