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As chaotic systems are widely used in many fields, the study of them is becoming more and more in- depth. This paper first presents a new single-equilibrium chaotic system which is only three terms, and some fundamental dynamical feature of the new chaotic system are discussed, such as equilibria, dissipativity, Poincaré diagram, bifurcation graph, etc. Secondly, a new finite-time controllers is designed by using Lyapunov stability theory, and it can be used for bound synchronization of the general chaotic systems. In contrast to the current finite time controller of the chaotic system, the designed controller in this paper does not contain exponential term, it can be simple and eliminate the chattering phenomenon during synchronizationis, which may be easier to implement in practical application. In addition, under the finite time controller, the bound of control energy consumption of the chaotic system is estimated. Finally, the finite-time controllers for the new chaotic system are advanced using the design method of finite-time controller of the general chaotic system, and the result of numerical simulation is given to check its validity by the designed method.

Computer-aided diagnosis (CAD) of pulmonary nodules is an effective approach for early detection of lung cancers, and pulmonary nodule classification is one of the key issues in the CAD system. However, CAD has the problems of low accuracy and high false-positive rate (FPR) on pulmonary nodule classification. To solve these problems, a novel method using intelligent immune clonal selection and classification algorithm is proposed and developed in this work. First, according to the mechanism and characteristics of chaotic motion with a logistic mapping, the proposed method utilizes the characteristics of chaotic motion and selects the control factor of the optimal chaotic state, to generate an initial population with randomness and ergodicity. The singleness problem of the initial population of the immune algorithm was solved by the proposed method. Second, considering on the characteristics of Gaussian mutation operator (GMO) with a small scale, and Cauchy mutation operator (CMO) with a big scale, an intelligent mutation strategy is developed, and a novel control factor of the mutation is designed. Therefore, a Gauss-Cauchy hybrid mutation operator is designed. Ultimately, in this study, the intelligent immune clonal optimization algorithm is proposed and developed for pulmonary nodule classification. To verify its accuracy, the proposed method was used to analyze 90 CT scans with 652 nodules. The experimental results revealed that the proposed method had an accuracy of 97.87% and produced 1.52 false positives per scan (FPs/scan), indicating that the proposed method has high accuracy and low FPR.

This paper investigates the finite-time synchronization of complex dynamical networks with nondelayed and delayed coupling. By designing a simple continuous function controller, sufficient criteria for finite-time synchronization of dynamical networks with nondelayed and delayed coupling are obtained. As a special case, the continuous function controller designed in this paper may be the simplest and easy to implement for the finite-time synchronization of dynamical networks without delay. Finally, numerical simulations are given to verify the effectiveness of the conclusions presented in this paper.

The objective of this paper is to discuss finite-time bounded synchronization for a class of the growing complex network with nondelayed and delayed coupling. In order to realize finite-time synchronization of complex networks, a new finite-time stable theory is proposed; effective criteria are developed to realize synchronization of the growing complex dynamical network in finite time. Moreover, the error of two growing networks is bounded simultaneously in the process of finite-time synchronization. Finally, some numerical examples are provided to verify the theoretical results established in this paper.

This paper investigates the problem of two kinds of function projective synchronization of financial chaotic system with definite integration scaling function, which are not fully considered in the existing research. Different from the previous methods, in this paper, the following two questions are investigated: (1) two kinds of the definite integration scaling function projective synchronization are given; (2) the upper and lower limit of the definite integral scaling function are the bound dynamical systems. Finally, illustrative example is provided to show the effectiveness of this method.

We investigate the problem of adaptive mean square synchronization for nonlinear delayed coupled complex networks with stochastic perturbation. Based on the LaSalle invariance principle and the properties of the Weiner process, the controller and adaptive laws are designed to ensure achieving stochastic synchronization and topology identification of complex networks. Sufficient conditions are given to ensure the complex networks to be mean square synchronization. Furthermore, numerical simulations are also given to demonstrate the effectiveness of the proposed scheme.