Detection and Location of Multi-Period Phenomena in Chaotic Binary Sequences

Due to the influence of finite calculation accuracy and binary quantization method, the performance of chaotic binary sequences has been degraded in varying degrees, and some sequences emerge as multi-period phenomena. Aiming at the problem that it is difficult to accurately detect this phenomenon, this paper proposes a multi-period positioning algorithm (MPPA), which can accurately detect and locate the accurate period and local period phenomena contained in chaotic binary sequences. In order to test the effectiveness and correctness of the algorithm, the multi-period characteristics of logistic binary sequences with different calculation accuracy are analyzed. MPPA evaluates the randomness of binary sequences from a new perspective, which provides a new idea for the analysis of cryptographic security of chaotic sequences.     

关于渐近随机的GFSR序列的设计

Ｔｏｏｔｉｌｌ等人提出了一种渐近的随机Ｔａｕｓｗｏｒｔｈｅ序列,并给出了一个偶然发现的此种序列,但直到现在尚未有人提出一个寻求此种序列的系统性的方法,本文中我们将给出一种设计ＧＦＳＲ序 算法,所产生的序列近似地满足渐近随机性,我们的算法基于反复地运用由Ｆｕｓｈｉｍｉ提出的算法,由现在的算法所设计出来的序列不有一种附加的好处,即其十中抽一的序列也是近似地渐近随机的,文中给出了一些数字例子。     

Computational Aspects of Optional Pólya Tree

Optional Pólya tree (OPT) is a flexible nonparametric Bayesian prior for density estimation. Despite its merits, the computation for OPT inference is challenging. In this article, we present time complexity analysis for OPT inference and propose two algorithmic improvements. The first improvement, named limited-lookahead optional Pólya tree (LL-OPT), aims at accelerating the computation for OPT inference. The second improvement modifies the output of OPT or LL-OPT and produces a continuous piecewise linear density estimate. We demonstrate the performance of these two improvements using simulated and real date examples.     

Recursive parameter identification for fermentation processes with the multiple model technique

This paper considers parameter identification problems for a fermentation process. Since the fermentation process is nonlinear, it is difficult to use a single-model for describing such a process and thus we use the multiple model technique to study the identification methods. The basic idea is to establish the model of the fermentation process at each operation point by means of the least squares principle, to obtain multiple models with different points, and then use the weighting functions or interpolation methods to compute the total model or the global model. Finally, a numerical example is provided to test the effectiveness of the proposed algorithm.     

The mixed-spins 1/2 and 3/2 Blume—Capel model with a random crystal field

The random crystal field(RCF) effects are investigated on the phase diagrams of the mixed-spins 1/2 and 3/2 Blume-Capel(BC) model on the Bethe lattice.The bimodal random crystal field is assumed and the recursion relations are employed for the solution of the model.The system gives only the second-order phase transitions for all values of the crystal fields in the non-random bimodal distribution for given probability.The randomness does not change the order of the phase transitions for higher crystal field values,i.e.,it is always second-order,but it may introduce first-order phase transitions at lower negative crystal field values for the probability in the range about 0.20 and 0.45,which is only the second-order for the non-random case in this range.Thus our work claims that randomness may be used to induce first-order phase transitions at lower negative crystal field values at lower probabilities.     

Performance analysis of a discrete-time Geo/G/1 queue with randomized vacations and at most J vacations

This paper presents the analysis of a discrete-time Geo/G/1$\mathit{Geo}/G/1$ queue with randomized vacations. Using the probability decomposition theory and renewal process, two variants on this model, namely the late arrival system with delayed access (LAS-DA) and early arrival system (EAS), have been examined. For both the cases, recursive solution for queue length distributions at arbitrary, just before a potential arrival, pre-arrival, immediately after potential departure, and outside observer’s observation epochs are obtained. Further, various performance measures such as potential blocking probability, turned-on period, turned-off period, vacation period, expected length of the turned-on circle period, average queue length and sojourn time, etc. have been presented. It is hoped that the results obtained in this paper may provide useful information to designers of telecommunication systems, practitioners, and others.     

Auxiliary model based parameter estimation for dual-rate output error systems with colored noise

The dual-rate sampled-data systems can offer better quality of control than the systems with single sampling rate in practice. However, the conventional identification methods run in the single-rate scheme. This paper focuses on the parameter estimation problems of the dual-rate output error systems with colored noises. Based on the dual-rate sampled and noise-contaminated data, two direct estimation algorithms are addressed: the auxiliary model based recursive extended least squares algorithm and the recursive prediction error method. The auxiliary model is employed to estimate the noise-free system output. An example is given to test and illustrate the proposed algorithms.     

Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling

This paper decomposes a Hammerstein nonlinear system into two subsystems, one containing the parameters of the linear dynamical block and the other containing the parameters of the nonlinear static block, and presents a hierarchical multi-innovation stochastic gradient identification algorithm for Hammerstein systems based on the hierarchical identification principle. The proposed algorithm is simple in principle and easy to implement on-line. A simulation example is provided to test the effectiveness of the proposed algorithm.