A secure and efficient entropy coding based on arithmetic coding

A novel security arithmetic coding scheme based on nonlinear dynamic filter (NDF) with changeable coefficients is proposed in this paper. The NDF is employed to generate the pseudorandom number generator (NDF-PRNG) and its coefficients are derived from the plaintext for higher security. During the encryption process, the mapping interval in each iteration of arithmetic coding (AC) is decided by both the plaintext and the initial values of NDF, and the data compression is also achieved with entropy optimality simultaneously. And this modification of arithmetic coding methodology which also provides security is easy to be expanded into the most international image and video standards as the last entropy coding stage without changing the existing framework. Theoretic analysis and numerical simulations both on static and adaptive model show that the proposed encryption algorithm satisfies highly security without loss of compression efficiency respect to a standard AC or computation burden.     

A novel chaotic encryption scheme based on arithmetic coding

In this paper, under the combination of arithmetic coding and logistic map, a novel chaotic encryption scheme is presented. The plaintexts are encrypted and compressed by using an arithmetic coder whose mapping intervals are changed irregularly according to a keystream derived from chaotic map and plaintext. Performance and security of the scheme are also studied experimentally and theoretically in detail.     

A model for real-time failure prognosis based on hidden Markov model and belief rule base

As one of most important aspects of condition-based maintenance (CBM), failure prognosis has attracted an increasing attention with the growing demand for higher operational efficiency and safety in industrial systems. Currently there are no effective methods which can predict a hidden failure of a system real-time when there exist influences from the changes of environmental factors and there is no such an accurate mathematical model for the system prognosis due to its intrinsic complexity and operating in potentially uncertain environment. Therefore, this paper focuses on developing a new hidden Markov model (HMM) based method which can deal with the problem. Although an accurate model between environmental factors and a failure process is difficult to obtain, some expert knowledge can be collected and represented by a belief rule base (BRB) which is an expert system in fact. As such, combining the HMM with the BRB, a new prognosis model is proposed to predict the hidden failure real-time even when there are influences from the changes of environmental factors. In the proposed model, the HMM is used to capture the relationships between the hidden failure and monitored observations of a system. The BRB is used to model the relationships between the environmental factors and the transition probabilities among the hidden states of the system including the hidden failure, which is the main contribution of this paper. Moreover, a recursive algorithm for online updating the prognosis model is developed. An experimental case study is examined to demonstrate the implementation and potential applications of the proposed real-time failure prognosis method.     

A chaotic secure communication scheme based on observer

Based on parameter modulation theory, an observer is presented to identify the unknown parameter of Liu chaotic system, then the useful information modulated in the parameter can be recovered successfully. Numerical simulations show the effectiveness of our method.     

Finite coding factors of Markov generators

Using Thouvenot’s relativized isomorphism theory, the author develops a conditionalized version of the Friedman—Ornstein result on Markov processes. This relativized statement is used to study the way in which a factor generated by a finite length stationary coding sits in a Markov process. All such factors split off if they are maximal in entropy. Moreover, one can show that if a finite coding factor fails to split off, it is relatively finite in a larger factor which either generates or itself splits off.     

Finitary coding of Markov random fields

Summary There exists a finitary code from any stationary ergodic Markov random field to any i.i.d. random field of strictly lower entropy.     

An improved customer lifetime value model based on Markov chain

Firms are increasingly looking to provide a satisfactory prediction of customer lifetime value (CLV), a determining metric to target future profitable customers and to optimize marketing resources. One of the major challenges associated with the measurement of CLV is the choice of the appropriate model for predicting customer value because of the large number of models proposed in the literature. Earlier models to forecast CLV are relatively unsuccessful, whereas simple models often provide results which are equivalent or even better than sophisticated ones. To predict CLV, Rust et al. (2011) proposed a framework model that performs better than simple managerial heuristic models, but its implementation excludes cases where customer's profit is negative and does not handle lost‐for‐good situations. In this paper, we propose a modified model that handles both negative and positive profits based on Markov chain model (MCM), hence offering a greater flexibility by covering always‐a‐share and lost‐for‐good situations. The proposed model is compared with the Pareto/Negative Binomial Distribution (Pareto/NBD), the Beta Geometric/Negative Binomial Distribution (BG/NBD), the MCM, and the Rust et al. (2011) models. Based on customer credit card transactions provided by the North African retail bank, an empirical study shows that the proposed model has better forecasting performance than competing models. Copyright © 2014 John Wiley & Sons, Ltd.     

A chaos secure communication scheme based on multiplication modulation

A secure spread spectrum communication scheme using multiplication modulation is proposed. The proposed system multiplies the message by chaotic signal. The scheme does not need to know the initial condition of the chaotic signals and the receiver is based on an extended Kalman filter (EKF). This signal encryption scheme lends itself to cheap implementation and can therefore be used effectively for ensuring security and privacy in commercial consumer electronics products. To illustrate the effectiveness of the proposed scheme, a numerical example based on Genesio-Tesi system and also Chen dynamical system is presented and the results are compared.     

A minimax model and arithmetic for initial emission permits

To carry the traffic of emission permits into execution, the main problem is how to allocate the initial emission permits. In the condition that the auction and pricing selling of the initial tradable emission permits have obstacle in practice, it is deemed that free allocation of initial tradable emission permits has operation in academia and practice. In this paper, based on economy efficiency and fair principle, we propose a minimax model of initial emission permits. Furthermore, a Karush-KuhnTucker optimality condition and a Newton method to solve the model are given. We consider the case when the correlative functions are nondifferentiable as well as we can make a tradeoff between the economy benefit and fairness according to the model.     

基于动态规划的高阶隐马氏模型推广的Viterbi算法

首先通过Hadar等价变换方法将高阶隐马氏模型转换为与之等价的一阶向量值隐马氏模型,然后利用动态规划原理建立了一阶向量值隐马氏模型的Viterbi算法,最后通过高阶隐马氏模型和一阶向量值隐马氏模型之间的等价关系建立了高阶隐马氏模型基于动态规划推广的Viterbi算法．研究结果在一定程度上推广了几乎所有隐马氏模型文献中所涉及到的解码问题的Viterbi算法,从而进一步丰富和发展了高阶隐马氏模型的算法理论．     

A contagion model with Markov regime-switching intensities

We consider a two-dimensional reduced form contagion model with regime-switching interacting default intensities. The model assumes the intensities of the default times are driven by macro-economy described by a homogeneous Markov chain as well as the other default. By using the idea of ＇change of measure＇ and some closed-form formulas for the Laplace transforms of the integrated intensity processes, we derive the two-dimensional conditional and unconditional joint distributions of the default times. Based on these results, we give the explicit formulas for the fair spreads of the first-to-default and second-to-default credit default swaps （CDSs） on two underlyings.     

Chaotic secure communication based on particle filtering

Applying the particle filtering technique, this paper considers the problem of chaotic secure communication. Even if there exist system noise and measurement noise in chaotic maps, the modulated messages can be estimated by a modified particle filter algorithm, i.e. a particle filter with message estimation. Furthermore, the driving signal can be arbitrarily nonlinear, which improves the security level for communication. Simulation results of Holmes map verify our main result.     

Chaotic secure communication based on particle filtering

Applying the particle filtering technique, this paper considers the problem of chaotic secure communication. Even if there exist system noise and measurement noise in chaotic maps, the modulated messages can be estimated by a modified particle filter algorithm, i.e. a particle filter with message estimation. Furthermore, the driving signal can be arbitrarily nonlinear, which improves the security level for communication. Simulation results of Holmes map verify our main result.     

A wild model of linear arithmetic and discretely ordered modules

Linear arithmetics are extensions of Presburger arithmetic () by one or more unary functions, each intended as multiplication by a fixed element (scalar), and containing the full induction schemes for their respective languages. In this paper, we construct a model of the 2‐linear arithmetic (linear arithmetic with two scalars) in which an infinitely long initial segment of “Peano multiplication” on is ‐definable. This shows, in particular, that is not model complete in contrast to theories and that are known to satisfy quantifier elimination up to disjunctions of primitive positive formulas. As an application, we show that , as a discretely ordered module over the discretely ordered ring generated by the two scalars, does not have the NIP, answering negatively a question of Chernikov and Hils.     

A more secure parallel keyed hash function based on chaotic neural network

Although various hash functions based on chaos or chaotic neural network were proposed, most of them can not work efficiently in parallel computing environment. Recently, an algorithm for parallel keyed hash function construction based on chaotic neural network was proposed [13]. However, there is a strict limitation in this scheme that its secret keys must be nonce numbers. In other words, if the keys are used more than once in this scheme, there will be some potential security flaw. In this paper, we analyze the cause of vulnerability of the original one in detail, and then propose the corresponding enhancement measures, which can remove the limitation on the secret keys. Theoretical analysis and computer simulation indicate that the modified hash function is more secure and practical than the original one. At the same time, it can keep the parallel merit and satisfy the other performance requirements of hash function, such as good statistical properties, high message and key sensitivity, and strong collision resistance, etc.     

A switch-modulated method for chaos digital secure communication based on user-defined protocol

In this paper, a scheme for digital secure communication is proposed. In this scheme, we use a control function which is defined by two communicants based on chaos synchronization. At first, different signals are sent according to the promissory transmission situation of control signal, then transmission field which is consist of protocol and transmission content is produced. After these processing, the correlation of the transmitted signals are decreased. In addition, the using of the compound non-linear function transformation can further intercalate the secret key, so a determined intruder is very difficult to retrieve the message using forecasting method.     

A higher-order Markov model for the Newsboy's problem

Markov models are commonly used in modelling many practical systems such as telecommunication systems, manufacturing systems and inventory systems. However, higher-order Markov models are not commonly used in practice because of their huge number of states and parameters that lead to computational difficulties. In this paper, we propose a higher-order Markov model whose number of states and parameters are linear with respect to the order of the model. We also develop efficient estimation methods for the model parameters. We then apply the model and method to solve the generalised Newsboy's problem. Numerical examples with applications to production planning are given to illustrate the power of our proposed model.     

A hidden Markov regime-switching model for option valuation

We investigate two approaches, namely, the Esscher transform and the extended Girsanov’s principle, for option valuation in a discrete-time hidden Markov regime-switching Gaussian model. The model’s parameters including the interest rate, the appreciation rate and the volatility of a risky asset are governed by a discrete-time, finite-state, hidden Markov chain whose states represent the hidden states of an economy. We give a recursive filter for the hidden Markov chain and estimates of model parameters using a filter-based EM algorithm. We also derive predictors for the hidden Markov chain and some related quantities. These quantities are used to estimate the price of a standard European call option. Numerical examples based on real financial data are provided to illustrate the implementation of the proposed method.