TDOA Passive Location Based on Cuckoo Search Algorithm

This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time difference of arrival(TDOA). With the application of the Levy flight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization(PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram′er-Rao lower bound(CRLB) and quickly achieve the global optimal solutions.     

Adaptive Sliding-Mode Tracking Control for an Uncertain Nonlinear SISO Servo System with a Disturbance Observer

An adaptive sliding mode controller with a disturbance observer (ASMC-DO) is proposed for the control of a single-input and single-output (SISO) servo system which has uncertain parameters, nonlinear friction, disturbance and input saturation. It is difficult to choose the suitable value of the parameters. The newly designed adaptive method is used to reduce the effects of system time-varying parameters, such as the moment of inertia and the damp coefficient. The robustness of object is improved. A DO is selected to approximate the compound disturbance and to render the estimate error convergent in finite time. The stability and the convergence of the closed-loop system are proved by using the Lyapunov theory. Experimental results show that the proposed ASMC-DO can better satisfy the influence of variable parameters and external disturbance to the control precision of the SISO servo system than other two controllers. The effectiveness of the proposed controller is showed. The control input stability and robust performances of the input saturation system are enhanced and the chattering is reduced.     

Adaptive Multi-Objective Optimization of Bionic Shoulder Joint Based on Particle Swarm Optimization

To get the movement mode and driving mechanism similar to human shoulder joint, a six degrees of freedom (DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators (PMAs) was designed. However, the structural parameters of the shoulder joint will affect various performances of the mechanism. To obtain the optimal structure parameters, the particle swarm optimization (PSO) was used. Besides, the mathematical expressions of indexes of rotation ranges, maximum bearing torque, discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics. And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method. The normalization method and adaptive-weight method were used to determine each optimization index’s weight coefficient; then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained. Compared with the average optimization generations and the optimal target values of many experiments, using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method, which validates superiority of the adaptive-weight method.     

Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method

Weight reduction has attracted much attention among ship designers and ship owners. In the present work, based on an improved bi-directional evolutionary structural optimization (BESO) method and surrogate model method, we propose a hybrid optimization method for the structural design optimization of beam-plate structures, which covers three optimization levels: dimension optimization, topology optimization and section optimization. The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints. The kernel optimization procedure (KOP) uses BESO to obtain the optimal topology from a ground structure. To deal with beam-plate structures, the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure. In the first optimization level, a series of ground structures are generated based on different dimensional parameter combinations, the KOP is performed to all the ground structures, the response surface model of optimal objective values and dimension parameters is created, and then the optimal dimension parameters can be obtained. In the second optimization level, the optimal topology is obtained by using the KOP according to the optimal dimension parameters. In the third optimization level, response surface method (RSM) is used to determine the section parameters. The proposed method is applied to a hatch cover structure design. The locations and shapes of all the structural members are determined from an oversized ground structure. The results show that the proposed method leads to a greater weight saving, compared with the original design and genetic algorithm (GA) based optimization results.     

GNN-CRC: Discriminative Collaborative Representation-Based Classification via Gabor Wavelet Transformation and Nearest Neighbor

Collaborative representation-based classification (CRC) is a distance based method, and it obtains the original contributions from all samples to solve the sparse representation coefficient. We find out that it helps to enhance the discrimination in classification by integrating other distance based features and/or adding signal preprocessing to the original samples. In this paper, we propose an improved version of the CRC method which uses the Gabor wavelet transformation to preprocess the samples and also adapts the nearest neighbor (NN) features, and hence we call it GNN-CRC. Firstly, Gabor wavelet transformation is applied to minimize the effects from the background in face images and build Gabor features into the input data. Secondly, the distances solved by NN and CRC are fused together to obtain a more discriminative classification. Extensive experiments are conducted to evaluate the proposed method for face recognition with different instantiations. The experimental results illustrate that our method outperforms the naive CRC as well as some other state-of-the-art algorithms.     

Simulation Study on Multi-Rate Time-Frequency Analysis of Non-Stationary Signals

A new time-frequency analysis method is proposed in this study using a multi-rate signal decomposition technique for the analysis of non-stationary signals. The method uses a multi-rate filter bank for an improved non-stationary signal decomposition treatment, and uses the Wigner-Ville distribution (WVD) analysis for signal reconstruction. The method presented in this study can effectively resolves the time and frequency resolution issue for non-stationary signal analysis and the cross-term issue typically encountered in time-frequency analysis. The feasibility and accuracy of the proposed method are evaluated and verified in a numerical simulation.     

Multi-Band Hybrid Mobile Phone Antenna Based on Electromagnetic Coupling

This research presents a multi-band hybrid mobile phone antenna based on electromagnetic coupling,which can be applied to mobile handheld devices, occupying a small board space of 39.7 mm × 15.6 mm on the system circuit board. By adding resonant and coupled branch instead of multi-feed on the traditional bent antenna,this design provides four wide operating bands of 0.772—0.998 GHz, 1.540—1.600 GHz, 1.680—2.270 GHz and2.300—2.690 GHz with the hybrid feature of planar inverted-F antenna(PIFA), L-shape, U-shape and S-shape structures, which cover nine-band, i.e., GSM850, GSM900, GPS1575, DCS1800, PCS1900, IMT200, LTE2300,LTE2600 and Blue Tooth/Wi-Fi. Ansoft software HFSS is used in this research to make the antenna performance better and the operating principle of the proposed antenna is described in detail. Result of simulation reveals that the maximum gains of these four wide bands are 2.20,-0.99, 4.01 and 4.05 dBi, respectively. Moreover, this research also tests the return loss(S11) of the fabricated antenna with the vector network analyzer and the result is in accordance with the simulation result on the whole. There are four wide resonant frequencies which cover nine-band of wireless wide area network(WWAN), wireless local area network(WLAN) and long term evolution(LTE), when the available bandwidth is better than 6 d Bi return loss.     

Effects of Heat Intensity and Inflow Wind on the Reactive Pollution Dispersion in Urban Street Canyon

This paper investigates the impacts of heating intensity and inflow wind speed on the characteristics of reactive pollutant dispersion in street canyons using the computational fluid dynamic (CFD) model that includes the transportation of NO, NO₂, and O₃ coupled with NO-NO₂-O₃ photochemistry. The results indicated that the heat intensity and inflow wind speed have a significant influence on the flow field, temperature field and the characteristics of reactive pollutant dispersion in and above the street canyon. With the street canyon bottom heating intensity increasing, NO, NO₂ and O₃ concentrations in street canyon are decreased. The O₃ concentration reductions are even more than the NO and NO₂ concentrations. Improving the inflow wind speed can significantly reduce the NO and NO₂ concentrations within street canyons. But the O₃ concentrations have a slight rise with wind speed increasing. The results would be useful for understanding the interrelation among reactive vehicle emissions, and provide references for urban planners.     

Research on Spatially Adaptive High-Order Total Variation Model for Weak Fluorescence Image Restoration

Photoacoustic imaging acquires the absorption contrast of biological tissue with ultrasound resolution. It has been broadly investigated in biomedicine for animal and clinical studies. Recently, a micro-electro-mechanical system (MEMS) scanner has been utilized in photoacoustic imaging systems to enhance their performance and extend the realm of applications. The review provides a recap of recent developments in photoacoustic imaging using MEMS scanner, from instrumentation to applications. The topics include the design of MEMS scanner, its use in photoacoustic microscopy, miniature imaging probes, development of dual-modality systems, as well as cutting-edge bio-imaging studies.