Item recognition has become a hotspot in the field of computer vision research. SIFT has the advantage of requiring a low amount of information, a fast running speed and high precision, but it requires large data calculations and thus takes a long time to perform the item recognition. In this paper we propose a method of item recognition based on SIFT and SURF that provides a new way to solve the problem of item recognition, and has both feasibility and availability. This technique currently ignores colour information when dealing with colour images, but the evaluation method is capable of taking colour quality characteristics into account so it should be possible to improve the algorithm in the future. Experimental results show that this system of item recognition based on the SURF algorithm gives better matching recognition, is faster and has greater robustness.

In this paper, we investigate the problem of robust stability for a class of delayed neural networks of neutral-type with linear fractional uncertainties. The activation functions are assumed to be unbounded, non-monotonic and non-differentiable, and the delay is assumed to be time-varying and belonging to a given interval, which means that the lower and upper bounds of the interval time-varying delay are available. By constructing a general form of the Lyapunov–Krasovskii functional, and using the linear matrix inequality (LMI) approach, we derive several delay-dependent stability criteria in terms of LMI. Finally, we give a number of examples to illustrate the effectiveness of the proposed method.

The function of airport gate assignment is to assign appropriate gates for arrival and departure flights and to ensure the flights are on schedule. A key task of airport ground operations is assigning the airport gate with high efficiency and a reasonable arrangement. In this paper we establish an optimised model based on the characteristics of both the flights (the flight type, flight down time and the number of passengers) and the airport gates (the ease of access of the airport gate). We give a representation of the solution space and a direct graph model of the airport gate configuration based on dynamic scheduling parallel machines. We design a method for solving the airport gate configuration based on an immune genetic algorithm. The simulation results show the effectiveness of this model and algorithm.

In this paper we make an empirical comparison of sales time series for online and offline channels. In particular, we analyse the sales dynamic and fluctuation level underlying the sales time series in different channels. The accumulative daily sales distributions of commodities are analysed statistically and the daily sales series are also studied from the perspective of complex networks. We find that most of the commodities' accumulative sales distributions can be fitted by power-law distributions. Visibility graphs are constructed for the daily sales series, and the accumulative degree distributions are also investigated – it is found that they also almost follow power-law distribution. The constant parameter α indicates that different specifications of the same goods have different sales characteristics, and different forms of packaging of commodities, either special offer or ordinary, also show distinctive sales fluctuation levels. The differences show that the direction of these relationships is opposite for online and offline channels.

The original software reliability demonstration test (SRDT) does not take adequate account of prior knowledge or the prior distribution, which can lead to an expensive use of many resources. In the current paper, we propose a new improved Bayesian based SRDT method. We begin by constructing a framework for the SRDT scheme, then we use decreasing functions to construct the prior distribution density functions for both discrete and continuous safety-critical software, and then present schemes for both discrete and continuous Bayesian software demonstration functions (which we call DBSDF and CBSDF, respectively). We have carried out a set of experiments comparing our new schemes with the classic demonstration testing scheme on several published data sets. The results reveal that the DBSDF and CBSDF schemes are both more efficient and more applicable, and this is especially the case for safety-critical software with high reliability requirements.

We model the transmission of a message on the complete graph with n vertices and limited resources. The vertices of the graph represent servers that may broadcast the message at random. Each server has a random emission capital that decreases at each emission. Quantities of interest are the number of servers that receive the information before the capital of all the informed servers is exhausted and the exhaustion time. We establish limit theorems (law of large numbers, central limit theorem and large deviation principle), as n → ∞, for the proportion of informed vertices before exhaustion and for the total duration. The analysis relies on a construction of the transmission procedure as a dynamical selection of successful nodes in a Galton–Watson tree with respect to the success epochs of the coupon collector problem.

We propose an adaptive genetic algorithm (AGA) for the multi-objective optimisation design of a fuzzy PID controller and apply it to the control of an active magnetic bearing (AMB) system. Unlike PID controllers with fixed gains, a fuzzy PID controller is expressed in terms of fuzzy rules whose consequences employ analytical PID expressions. The PID gains are adaptive and the fuzzy PID controller has more flexibility and capability than conventional ones. Moreover, it can be easily used to develop a precise and fast control algorithm in an optimal design. An adaptive genetic algorithm is proposed to design the fuzzy PID controller. The centres of the triangular membership functions and the PID gains for all fuzzy control rules are selected as parameters to be determined. We also present a dynamic model of an AMB system for axial motion. The simulation results of this AMB system show that a fuzzy PID controller designed using the proposed AGA has good performance.

We consider a class of uncertain non-linear systems preceded by unknown backlash-like hysteresis, which is modelled by a differential equation. We propose a new state feedback robust adaptive control scheme using a backstepping technique and properties of the differential equation. In this control scheme, we construct a new continuous function to design an estimator to estimate the unknown constant parameters and the unknown bound of a ‘disturbance-like’ term. The transient performance of the output tracking error can be guaranteed by the introduction of pre-estimates of the unknown parameters in our controller together with update laws. We do not require bounds on the ‘disturbance-like’ term or unknown system parameters in this scheme. The global stability of the closed-loop system can be proved.

This paper addresses the H∞ state feedback stabilisation problem for networked control systems (NCSs) in the presence of time delays and packet losses. By introducing the concept of an effective sensor packet, the NCS is transformed into a new discrete-time switched model, where the parameters have a clear physical meaning and can be easily determined. In this framework, we derive the stability conditions of the closed-loop system in the H∞ sense, and also provide the corresponding H∞ stabilising controller design method. Finally, we give simulation and experimental results to demonstrate the effectiveness of the proposed approaches.

In recent years, under the dual pressure of environmental requirements and a series of conventional energy shortages, including power cuts, coal shortages and rising oil prices, there have been unprecedented opportunities for clean energy, and especially for the development and utilisation of solar energy. Hence, solar products have become increasingly popular because of the energy saving and environmental protection they offer. China's solar energy industry should be in the self-development mechanism, which is market-oriented and should act as a mainstay for enterprises. Scientifically forecasting the potential of the solar energy industry and rationally evaluating its status as a result of a market economy-oriented development is an effective means of building a low-carbon and harmonious society. In the work reported in this paper, we:

• – established a comprehensive evaluation index system, covering natural resources, economic conditions, policy support, technology and the market environment;

• – constructed a GA-SA model based on analysing the principles of GA (genetic algorithms) and SA (simulated annealing); and

• – applied these tools to predicting the potential of the solar power industry.

In wireless broadband communication systems, the inherent non-linearity of power amplifiers creates spectral growth beyond the signal bandwidth, which interferes with adjacent channels. It also causes distortions within the signal bandwidth. In this paper, we study five digital predistortion algorithms for linearising two different non-linear memory power amplifier models. The simulation results show that the proposed digital predistorter using different algorithms can improve the in-band distortion and out of band spreading in different ways. In particular, the DLMS algorithm with fast convergence can significantly suppress spectral regrowth (by 60dB), effectively compensating for the non-linearity of the power amplifier.

Mathematical Structures in Computer Science bridges the gap between theoretical computer science and software design. By publishing original perspectives from all areas of computing, the journal stresses applications from logic, algebra, geometry, category theory and other areas of logic and mathematics. Through issues such as this special issue, the journal also plans to play an occasional, but important role in the fields of intelligent computation and automation.

We derive a delay-dependent H∞ performance criterion with a decoupled structure for systems with neutral time delay. We then extend it to an H∞ controller synthesis for systems with polytopic uncertainty. All conditions are given in terms of linear matrix inequalities (LMIs). In some previous descriptor system methods, the products of the controller and Lyapunov matrices are completely separated for the performance analysis, but not for controller synthesis - the method developed in the current paper eliminates this weakness. We present a numerical example to illustrate the effectiveness of the solution.