Yixian Yang

Synchronization control of memristor-based recurrent neural networks with perturbations.

In this paper, the synchronization control of memristor-based recurrent neural networks with impulsive perturbations or boundary perturbations is studied. We find that the memristive connection weights have a certain relationship with the stability of the system. Some criteria are obtained to guarantee that memristive neural networks have strong noise tolerance capability. Two kinds of controllers are designed so that the memristive neural networks with perturbations can converge to the equilibrium points, which evoke humans memory patterns. The analysis in this paper employs the differential inclusions theory and the Lyapunov functional method. Numerical examples are given to show the effectiveness of our results.

Hyperentanglement concentration for n-photon 2n-qubit systems with linear optics

Hyperentanglement involves multiple degrees of freedom of a quantum system and has attracted a lot of attention recently because of its high efficiency in quantum applications. We propose some practical schemes using linear optics for partially entangled n-photon 2n-qubit systems with spatial and polarization degrees of freedom. The states involved are not equivalent to the general Bell states or GHz states under local quantum operations and classical communication. Our schemes are based on the parameter-splitting method, which can change different entanglement coefficients into equal coefficients. They are very efficient and practical as they use only linear-optical elements and do not require nonlinear optics.

Multiple routes transmitted epidemics on multiplex networks

Abstract This letter investigates the multiple routes transmitted epidemic process on multiplex networks. We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemic can spread across the multiplex network even if all the network layers are well below their respective epidemic thresholds. Strong positive degree–degree correlation of nodes in multiplex network could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity of neighbors from different layers of nodes has no obvious effect on the epidemic threshold and outbreak size.

Controlled remote state preparation of arbitrary two and three qubit states via the Brown state

In this paper, several new protocols for the controlled remote state preparation (CRSP) by using the Brown state as the quantum channel are proposed. Firstly, we propose a CRSP protocol of an arbitrary two qubit state. Then, the CRSP protocol of an arbitrary three qubit state, which has rarely been considered by the previous papers, is investigated. The coefficients of the prepared states can be not only real, but also complex. To design these protocols, some useful and general measurement bases are constructed, which can greatly reduce the restrictions for the coefficients of the prepared states. The security analysis is provided in detail. Moreover, receiver’s all recovery operations are summarized into a concise formula.

Robust and Efficient Biometrics Based Password Authentication Scheme for Telecare Medicine Information Systems Using Extended Chaotic Maps

The Telecare Medicine Information Systems (TMISs) provide an efficient communicating platform supporting the patients access health-care delivery services via internet or mobile networks. Authentication becomes an essential need when a remote patient logins into the telecare server. Recently, many extended chaotic maps based authentication schemes using smart cards for TMISs have been proposed. Li et al. proposed a secure smart cards based authentication scheme for TMISs using extended chaotic maps based on Lee’s and Jiang et al.’s scheme. In this study, we show that Li et al.’s scheme has still some weaknesses such as violation the session key security, vulnerability to user impersonation attack and lack of local verification. To conquer these flaws, we propose a chaotic maps and smart cards based password authentication scheme by applying biometrics technique and hash function operations. Through the informal and formal security analyses, we demonstrate that our scheme is resilient possible known attacks including the attacks found in Li et al.’s scheme. As compared with the previous authentication schemes, the proposed scheme is more secure and efficient and hence more practical for telemedical environments.

An Enhanced Biometric-Based Authentication Scheme for Telecare Medicine Information Systems Using Elliptic Curve Cryptosystem

The telecare medical information systems (TMISs) enable patients to conveniently enjoy telecare services at home. The protection of patient’s privacy is a key issue due to the openness of communication environment. Authentication as a typical approach is adopted to guarantee confidential and authorized interaction between the patient and remote server. In order to achieve the goals, numerous remote authentication schemes based on cryptography have been presented. Recently, Arshad et al.(J Med Syst 38(12): 2014) presented a secure and efficient three-factor authenticated key exchange scheme to remedy the weaknesses of Tan et al.’s scheme (J Med Syst 38(3): 2014). In this paper, we found that once a successful off-line password attack that results in an adversary could impersonate any user of the system in Arshad et al.’s scheme. In order to thwart these security attacks, an enhanced biometric and smart card based remote authentication scheme for TMISs is proposed. In addition, the BAN logic is applied to demonstrate the completeness of the enhanced scheme. Security and performance analyses show that our enhanced scheme satisfies more security properties and less computational cost compared with previously proposed schemes.

Multi-party quantum secret sharing with the single-particle quantum state to encode the information

We present a three-party quantum secret sharing (QSS) scheme via the entangled Greenberger–Horne–Zeilinger state. In this scheme, the sender Alice encodes her arbitrary secret information by means of preparing a single-particle quantum state. The agent Bob obtains his shared information according to his hobby, while Charlie can easily calculate his shared information. The proposed scheme is secure. It is shown that even a dishonest agent, who may avoid the security checking, cannot obtain any useful information. Moreover, we further investigate the multi-party QSS scheme which allows most agents to predetermine their information.

Robust biometrics based authentication and key agreement scheme for multi-server environments using smart cards.

Biometrics authenticated schemes using smart cards have attracted much attention in multi-server environments. Several schemes of this type where proposed in the past. However, many of them were found to have some design flaws. This paper concentrates on the security weaknesses of the three-factor authentication scheme by Mishra et al. After careful analysis, we find their scheme does not really resist replay attack while failing to provide an efficient password change phase. We further propose an improvement of Mishra et al.’s scheme with the purpose of preventing the security threats of their scheme. We demonstrate the proposed scheme is given to strong authentication against several attacks including attacks shown in the original scheme. In addition, we compare the performance and functionality with other multi-server authenticated key schemes.

Chaos–order transition in foraging behavior of ants

Significance We have studied the foraging behavior of group animals that live in fixed colonies (especially ants) as an important problem in ecology. Building on former findings on deterministic chaotic activities of single ants, we uncovered that the transition from chaotic to periodic regimes results from an optimization scheme of the self-organization of such an animal colony. We found that an effective foraging of ants mainly depends on their nest as well as their physical abilities and knowledge due to experience. As an important outcome, the foraging behavior of ants is not represented by random, but rather by deterministic walks, in a random environment: Ants use their intelligence and experience to navigate. The study of the foraging behavior of group animals (especially ants) is of practical ecological importance, but it also contributes to the development of widely applicable optimization problem-solving techniques. Biologists have discovered that single ants exhibit low-dimensional deterministic-chaotic activities. However, the influences of the nest, ants’ physical abilities, and ants’ knowledge (or experience) on foraging behavior have received relatively little attention in studies of the collective behavior of ants. This paper provides new insights into basic mechanisms of effective foraging for social insects or group animals that have a home. We propose that the whole foraging process of ants is controlled by three successive strategies: hunting, homing, and path building. A mathematical model is developed to study this complex scheme. We show that the transition from chaotic to periodic regimes observed in our model results from an optimization scheme for group animals with a home. According to our investigation, the behavior of such insects is not represented by random but rather deterministic walks (as generated by deterministic dynamical systems, e.g., by maps) in a random environment: the animals use their intelligence and experience to guide them. The more knowledge an ant has, the higher its foraging efficiency is. When young insects join the collective to forage with old and middle-aged ants, it benefits the whole colony in the long run. The resulting strategy can even be optimal.

Data clustering using bacterial foraging optimization

Clustering divides data into meaningful or useful groups (clusters) without any prior knowledge. It is a key technique in data mining and has become an important issue in many fields. This article presents a new clustering algorithm based on the mechanism analysis of Bacterial Foraging (BF). It is an optimization methodology for clustering problem in which a group of bacteria forage to converge to certain positions as final cluster centers by minimizing the fitness function. The quality of this approach is evaluated on several well-known benchmark data sets. Compared with the popular clustering method named k-means algorithm, ACO-based algorithm and the PSO-based clustering technique, experimental results show that the proposed algorithm is an effective clustering technique and can be used to handle data sets with various cluster sizes, densities and multiple dimensions.