Design and Implementation of Chaos Encrytion Algorithm based on Logistic Formula

The security of stream cipher, which is known as one of the main cipher techniques, dependents completely on the quality of generated pseudo-stochastic sequences. Chaotic systems can produce the pseudo-stochastic sequences with the properties of excessive dependence on initial conditions and the difficulty in forecasting, therefore, these systems are suitable to the stream cipher. A new encryption algorithm is proposed by analyzing the principle of the chaos encryption algorithm based on logistic formula. Moreover, the security and performance of the proposed algorithm is also estimated. Finally, an example is given to demonstrate our method via the Visual C++.     

Chaotic Synchronization of Discrete Nonlinear Systems on Different Parameters for a Kind of Systems

According to the theory of parameters adaptive control and variable driving, for a kind of discrete nonlinear chaotic systems, a method of chaotic synchronization is presented for different system parameters. In the equation of parameters adaptive control, control coefficients are chaotic signal. Because control coefficients are constant usually for the former parameters adaptive control, so the parameters adaptive control method is very universal, namely the former parameters adaptive control methods are special examples in our control method. Simulation results show that this method is available.     

public-key Encryption Based on Torus Automorphisms

Chaotic maps with its characteristic are very useful in cryptography, however, compared with wide application in symmetric system, the research about chaos in public-key encryption system is still few. Through analysing the period of toms automorphisms which is a prototype of chaotic map, and making use of the framework of the traditional public-key algorithm RSA, the authors propose a chaotic public-key encryption algorithm based on toms automorphisms. Its security is based on the intractability of the integer factorization problem as RSA, and it is able to resist the chosen-ciphertext attack against RSA and easy to be implemented.     

An algorithm of image processing based on discrete wavelet transform compression and chaotic scrambling

An algorithm was proposed in view of the combination of image compression and encryption. We got the approximate part and three detail parts after transforming the image with discrete wavelet transform (DWT), and compressed the image by modifying the detail parts by a given threshold value based on human visual systems. And then, we encrypted the image by scrambling the approximate part because this part held mostly of the energy. Last, a compressed and encrypted image can be achieved after DWT. Simulation result shows a good effect on the combination of compression and encryption.     

Chaotic Time Series Analysis Based on Radial Basis Function Networks

A method based on radial basis function networks for forecasting chaotic time series is proposed.The nonlinear time series identification problem is formulated with a nonlinear autoregressive moving average(NARMAX)model then a new identification algorithm based on dynamic radial basis function networks is proposed.Then this method is applied to the estimation of embedding dimension for chaotic time series of Henon mapping and the confirmation of the chaotic phenomena in stock markets of China,from which one can get the desired results.Further research directions are also pointed out.     

Synchronization of Chaotic Systems Employing the Theory of Application of Linear Time-varying Impulsive Differential Equations

Employing the stability theory of linear non-autonomous impulsive differential equations, some sufficient conditions for the synchronization of unified chaotic systems and Lorenz chaotic systems are derived. This method can be applied to most of chaotic systems. The numerical simulations also demonstrate the efficiency of impulsive control.     

Exponential Stability Analysis for TS-model-based Fuzzy Chaotic Control Systems With Delays

The issue of exponential stability for TS-model-based fuzzy chaotic control systems with constant or time-varying delays is investigated. A linear-feedback fuzzy controller is designed using parallel dispersal compensation technique for a large class of chaotic control systems. By means of the Lyapunov-Krasovskii functional approach in combination of the linear matrix inequality and differential inequality techniques, the criteria for exponential stability of the TS-model-based fuzzy controller are derived, and the corresponding control laws are presented. The results are easy to be calculated numerically because of the linear matrix inequalities representation.     

基于混沌时间序列的马尾松角胫象林间诱捕数量短期预测

为了对马尾松角胫象的防治及松材线虫病的控制提供技术支持,利用混沌时间序列的基本原理,分析马尾松角胫象林间诱捕序列,并重构其相空间及计算最大Lyapunov指数。结果表明：马尾松角胫象林间诱捕序列具有混沌特性。在此基础上,应用加权一阶局域预测模型对马尾松角胫象种群动态进行短期预测,结果显示在最长可预报时间尺度内该模型的预测成功率为100%。     

Novel Image-adaptive Watermarking Algorithm

Digital watermarking is an effective method to provide copyright protection for digital media. A blind image- adaptive watermarking algorithm based on DCT domain is presented. The algorithm selects adaptively the step size of quantization to embed the watermark bits by modifying DC components via the human visual system model and local characteristics of image; at the same time some AC components of the blocks with less perceptual capacity are also modified to embed the same watermark bits by using quantization. Thus the relation between robustness and imperceptibility can be well balanced. The algorithm recovers the watermark without any reference to the original image. Compared with the similar algorithm reported in the literature, this method can give better image quality and is better robust against noise and commonly used image processing techniques.     

Learning Causality Diagram Structure Based on Genetic Algorithm

The Causality Diagram theory,which adopted graphical expression of knowledge and direct causality intensity of causality,overcomes some shortages in Belief Network and has evolved into a mixed causality diagram methodology coped with discrete and continuous variable.But it is difficult that the structure of Causality Diagram given by expert.Because the complexity of causality diagram structure goes up exponentially through the number of the vertex's increasing,it is NP-hard problem to find the most possible structure from a set of data.The authors discuss approaches and present Genetic Algorithm,to find the most possible structure from a set of data.Experiment shows the method is effective.     

Study of Multivariable Adaptive Fuzzy Control Algorithm With Hierarchical Structure

In this paper a class of multivariable fuzzy adaptive con trol algorithm withdecoupling design is propoed,The proposed simplification controller is based on the decompositiontheorem of muItivarinble fuzzy conditional statement andhierarchical multirules structure,Thefuzzy modification of controller's rule is achieved by looking for a medifiable coefficient table forrestraining disturbance.Simulation results demonstrate the effectiveness of the controller.     

New Iterative Decoding Algorithm of the Product Codes

It is very important to adopt a new index to evaluate me ratinality of energy consumption effectively, at the time to make great effort to reduce the energy consumption in water supply system. Current index of unit electricity consumption and integrated unit electricity consumption to assess the rationality of the energy consumption of the whole water supply system in our country cant be used to compare from landscape orientation. Aiming at the case, an index of efficiency is put forward on the base of analysis of the minimum energy that the water transportation in water supply system needs. According to the analysis of the index, the function to compare the energy consumption of different whole water supply systems of the index is proved.     

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.     

Distribution Network Structure Planning Based on Multi-population Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem, which is difficult to solve properly by using traditional optimization methods. The authors put forward Multiple Population Immune Genetic Algorithm (MPIGA)for optimal planning of distribution network structure, and do optimal search to different aspects of optimization goals. During the genetic evolution process, biologic immune mechanism is introduced to do some immune operator operation on chromosomes of each population, which can interact mutually by the shift of excellent units. By this way, it can effectively prevent population retrogression, promote diversity and the whole optimal searching ability of genetic algorithm. In order to minimize network annual expenditure, a mathematic model is established. The optimal solution is obtained by this algorithm, which has been illustrated effectively by specific examples at the same time.     

A Study on Chaotic State of EEG Signal

In this paper.the chaotic theory is described briefly and the chaotic state ofEEG on thinking are studied. In this study. the method of detecting short bursts of 40 Hz EEG ac-tivity is firstly usedto dedermine the segments to be computed for analysis of the chaotic state ofEEG. therefore the reliability and stability of the analysis results are assured In this paper.thechaotic para meters of qa n titative analysis are studied and more then 30 subjects EEG are analysedfor the value of the fractional dimension and the maximal Lyapunov exponent.The results of exper-iments indicate that the value of the fractional dimension is valuable for clincal diagnosis and themaximal Lyapunov exponent is not sufficient for dignosis of disease.