Focusing on the problem of solving coupled Logistic fractional-order differential equation, a discretization method was introduced to solve it discretly. Firstly, a coupled Logistic integer-order differential equation was introduced into the fields of fractional-order calculus. Secondly, the corresponding coupled Logistic fractional-order differential equation with piecewise constant arguments was analyzed and the proposed discretization method was applied to solve the model numerically. Then, according to the fixed point theory, the stability of the fixed point of the synthetic dynamic system was discussed, and the boundary equation of the first bifurcation of the coupled Logistic fractional-order system in the parameter space was given. Finally, the model was numerically simulated by Matlab, and more complex dynamics phenomena of model were discussed with Lyapunov index, phase diagram, time series diagram and bifurcation diagram. The simulation results show that, the proposed method is successful in discretizing coupled Logistic fractional-order differential equation.

A fuzzy multi-objective software reliability allocation model was established, and bacteria foraging optimization algorithm based on estimation of distribution was proposed to solve software reliability redundancy allocation problem. As the fuzzy target function, software reliability and cost were regarded as triangular fuzzy members, and bacterial foraging algorithm optimization based on Gauss distribution was applied. Different membership function parameters were set up, and different Pareto optimal solutions could be obtained. The experimental results show that the proposed swarm intelligence algorithm can solve multi-objective software reliability allocation effectively and correctly, Pareto optimal solution can help the decision between software reliability and cost.

To solve the problem that software implementation cannot meet real-time requirements, a hardware scheme based on Field-Programmable Gate Array (FPGA) was presented. By analyzing the digital watermark extraction system, a watermark-embedding algorithm suitable for FPGA implementation was designed and its structure is applicable to 5/3 wavelet transform. Moreover, a new watermark extraction structure that corresponded to the embedding algorithm was also proposed. The pipeline and highly parallel structure has the features of high computation efficiency, small size, low-power and real-time process. The simulation results demonstrate the system's correctness and the algorithm's abroad applicability.

In this paper, a kind of algorithm for all-zero block detection based on Radial Basis Function (RBF) Neural Network (NN) was proposed to improve the accuracy of all-zero block detection algorithm. By analyzing the H.264 encoder features, six effective features were selected, including Sum of Absolute Difference (SAD), Sum of Absolute Transformed Difference (SATD), block type, Rate Distortion Optimization (RDO) cost, Quantization Parameter (QP) and the situation of reference block. Considering the SATD should be used in the Hadamard Transform (HT), to get the relationship of QP and RBF network width parameter through the least square method, the algorithm used two classifiers to separate all-zero blocks from non-all-zero blocks based on the encoding situation of the reference block. This algorithm could improve coding speed over 50% on average while keeping bit rate and video quality almost unchanged. The experimental results show that the proposed algorithm can improve all-zero block detection accuracy effectively and coding efficiency based on NN.