Lequan Min

COLOR EDGE DETECTIONS BASED ON CELLULAR NEURAL NETWORK

Color edge detection is one of the most important steps for RGB image recognition. In this paper, we first present two robustness design theorems for the Edgegray Detection Cellular Neural Network (EDGE CNN) and the counter detection (CD) CNN. Second, based on a color plane transform of RGB image and the two theorems, we design a color EDGE CNN and a CD CNN. As applications, the two CNNs detect successfully the edges of a standard color edge test pattern, and two popular RGB images, respectively. Our findings show that CNN may provide a useful tool for color image processing.

A viral infection model with periodic immune response and nonlinear CTL response

This paper investigates a viral infection model with periodic immune response and nonlinear cytotoxic T lymphocyte (CTL) response. Using the periodic rhythms of human immune system, the model can avoid the unreasonable equilibrium in the basic viral model with nonlinear CTL response introduced by Nowak et al. We obtain the global stability of the infection-free equilibrium and the immune-exhausted equilibrium. Numerical simulations show that the oscillation of immune system can affect the pattern of the viral dynamical behaviors. Period doubling bifurcations of the system are observed via simulations. This can provide a possible interpretation for the viral oscillation behaviors, which were observed in chronic HBV and HCV infection patients.

Global Stability of Endemic Equilibrium Point of Basic Virus Infection Model with Application to HBV Infection

In this paper, the authors first show that if R0 ≤ 1, the infection free steady state is globally attractive by using approaches different from those given by Min, et al.(2008). Then the authors prove that if R0 > 1, the endemic steady state is also globally attractive. Finally, based on a patient’s clinical HBV DNA data of anti-HBV infection with drug lamivudine, the authors establish an ABVIM. The numerical simulations of the ABVIM are good in agreement with the clinical data.

Design for robustness edgegray detection CNN

The cellular neural/nonlinear network (CNN) is a powerful tool for image and video signal processing, robotic and biological vision. The paper sets up a theorem to design a robustness template CNN for edge gray detection in gray-scale, which provides parameter inequalities for determining parameter intervals for implementing the corresponding tasks. The edges in two different kinds of gray-scale image are successfully detected by the edgegray CNNs designed via the theorem.

The robustness design of templates of CNN for detecting inner corners of objects in gray-scale images

The paper presents a theorem for designing the robustness template parameters of cellular neural/nonlinear network (CNN) for extracting inner corners of objects in gray-scale images. The theorem provides parameter inequalities for determining parameter intervals for implementing the corresponding tasks. The designed CNN has a linear A-template and a nonlinear B-template with two thresholds. A first numerical simulation example shows that the CNN designed via our method successfully detects the inner corners of objects in gray-scale images. A second one implies that the inner corner detection CNN may extract inner corners of objects in gray-scale images with Gaussian noise if suitable thresholds of the CNN are chosen.

A Generalized Chaos Synchronization Theorem for Array Differential Equations with Application

A constructive generalized chaos synchronization (GS) theorem for unidirectionally coupled array ordinary differential equation systems (ADESs) is presented. Based on the theorem, one can design a GS driven ADES via a driving chaotic ADES and a C1 diffeomorphism. As an application, a Duffing cellular neural network (CNN) with four state variables is introduced. Using the GS theorem and the Duffing CNN constructs coupled GS ADESs with 3087 cells. The hyper chaotic GS phenomena of the GS ADESs have been simulated. The numerical simulation results display complex behaviors of the GS ADESs.

An image encryption scheme based on generalized synchronization theorem for discrete array systems

First this paper introduces a discrete Lorenz three-dimensional chaotic (Lorenz) Cellular Neural Network (CNN). Second based on a constructive generalized chaos synchronization (GS) theorem for unidirectionally coupled discrete array system (UCDAS) presented in, and the Lorenz CNN, this paper constructs a coupled GS UCDAS with 51times51times6 cells. The hyper chaotic GS phenomena of the GS UCDAS have been simulated. Third using the GS UCDAS designs an image encryption scheme with a function similar to one-time-pad. The scheme is sensitive to the perturbations of the parameters and the initial conditions of the UCDAS.The key space of the scheme is larger than 10281. The analysis of the key space, sensitivity of key parameters show that this scheme has sound security. Numerical simulations show that our scheme is effective to be used in secure communication.

Two Theorems on the Robust Designs for Dilation and Erosion CNNs

The cellular neural/nonlinear network (CNN) has become a new tool for image and signal processing, robotic and biological visions, and higher brain functions. Based our previous research, this paper set up two new theorems of robust designs for Dilation and Erosion CNNs processing gray-scale images, which provide parameter inequalities to determine parameter intervals for implementing prescribed image processing functions, respectively. Four numerical simulation examples for Dilation and Erosion CNNs are given to illustrate the effectiveness of our theorems.

Modeling and Simulation for Dynamics of Anti-HBV Infection Therapy

Based on our previous researches, this paper introduces a new differential equation model to describe the dynamics of traditional Chinese medicines (TCM) + nucleoside analogues (NA) anti-HBV infection treatment for the chronic hepatitis B (CHB) patients. This model has five state variables. A treatment-activated specific term in this model is in charge of directly clearing patients’ HBV rather than damaging patients’ hepatocytes. As an application, we use this model to simulate the dynamics of TCM + NA anti-HBV infection personalized combination treatments. The numerical simulations and analysis show that the TCM + NA combination treatments are able to activate patients’ abilities of cytokine-midiated noncytolytic HBV clearance.

A generalized chaos synchronization-based pseudorandom number generator and performance analysis

Based on a generalized chaos synchronization theorem for discrete-time systems, this paper introduces a new 4-dimensional generalized chaos synchronization system. A chaosbased pseudorandom number generator (CPNG) is designed based on the new system. We use the FIPA-140-2 tests issued by the National Institute of Standard and Technology to verify the random properties of the binary number sequences generated by the CPNG. The results showed that all binary number sequences passed the tests. The confidence interval analysis showed that the binary number sequences have sound random properties. Furthermore, the highly sensitivity to the seeds (initial conditions of the CPNG) may make the CPNG be used for “one-time-pad” communication.