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This paper studied the robust beamforming for dense transmission systems with imperfect channel state information (CSI). The objective was to maximize the minimum signal to interference plus noise ratio (SINR) in the constraint of the per base station (BS) power. By performing the uplink–downlink duality theory, the referred non-convex optimization problem can be changed into the equivalent uplink decoupling optimization problem. Then, we proposed the instantaneous updating uplink–downlink power algorithm, which relies on instantaneous CSI for the finite system. For the massive MIMO system, to obtain the solution to the problem required for power to instantaneously update, we proposed the updating uplink–downlink power algorithm, which only requires statistical CSI, by applying the random matrix theory. The simulation results show the feasibility and effectiveness of our proposed algorithms.

Wayside acoustic detection is a promising technology for railway-vehicle bearing health monitoring due to its merits of non-conduct measurement, low cost, and early warning capacity. However, the diagnostic accuracy will be reduced by the problems of strong background noise and Doppler distortion. Considering the super spatial directivity ability of the microphone array, in this paper, a uniform rectangular array (URA) and an optimal spatial filter (OSF) based on the principle of minimum variance distortion-less response (MVDR) are designed to improve the diagnostic accuracy. Compared with the traditional single microphone and linear array, spatial directivity can be improved significantly so that the better anti-noise performance and higher diagnostic accuracy can be achieved. First, a URA consisting of 15 microphone elements arranged into five columns and three rows is designed to capture the wayside acoustic signal. Second, the direction angle of the target moving sound source with high accuracy is calculated at different times. Third, an OSF based on the principle of the MVDR is designed to extract the target sound source signal. Fourth, Doppler effect embedded in the filtered signal is eliminated using the MVDR spectrum estimation and resampling method. Finally, the diagnosis decision is made through an envelope spectrum analysis. The comparative simulation and experimental case studies are carried out to verify the effectiveness and improvement of the proposed method.

Two segments of gold-layer filled photonic crystal fibers (PCF) are joined together to achieve localized Surface Plasmon Resonance (SPR) effect. The cladding air-holes of both two PCFs are selectively filled with magnetic fluid (MF) while only one PCF would be applied a transverse force. The optical field distributions and loss spectra at different wavelengths are calculated and simulated using the finite element method (FEM). Results show that a blue-shift of the loss peaks will be obtained with the increase of applied transverse force. Based on the dependence of the MF refractive index on temperature and magnetic field, the sensitivity of the spectral response of the device to magnetic field and temperature is characterized, and the results of its application as a dual-parameter PCF-based sensor are also presented.

The indoor and outdoor PM

For the problem with imprecise optimal solution and reduced convergence efficiency of basic artificial fish swarm algorithm (BAFSA) in the late, the adaptive enhanced prey behavior of artificial fish and the segmented adaptive strategy of artificial fish’s view and step were designed. The hybrid adaptive artificial fish swarm algorithm (HAAFSA) was structured by the adaptive enhanced prey behavior and the segmented adaptive strategy of artificial fish’s view and step, which have been verified on research. According to the characteristics of the coalmine rescue environment, the path planning environment model was established in two-dimensional plane and the optimization constraints conditions were disposed by detecting the distance between path sections and barriers. The HAAFSA was applied to coalmine rescue robot path planning. Simulation results showed that the HAAFSA could improve the performance of the optimal path.

Ultrasound image technology is to measure the energy and time of arrival of the reflected echo after the pulse acoustic signal is sent out by the ultrasonic wave. Usually, the distance between the ultrasonic source and the reflector is measured. Super-resolution image reconstruction aims to recover high-resolution images from one or more low-resolution images. Super-resolution image reconstruction is a software approach to solve the problem of low-resolution images by overcoming the limitations of hardware. In this paper, an image super-resolution reconstruction method based on sparse representation model and multi-feature fusion is proposed. Sparse dictionary is used to learn and reconstruct the luminance details of ultrasonic images, and edge interpolation is used to improve the edge clarity. Experimental results show that the proposed method is superior to Bicubic interpolation, SCSR and JOR in PSNR, and is 0.35 dB higher than RAISR. On the FSIM index, this method is also slightly better than other comparison methods, which can get better reconstruction results. Visual effects and numerical evaluation results of reconstructed images are better than several comparison methods.

The dual-color laser phenomena in two-dimensional (2D) scattering gain media was investigated by simultaneously solving Maxwell's equations and rate equations of electronic population. The results indicate that dual-color laser emission from a dye solution with scattering nanoparticles is affected by the number of density scatterers in the dye solution and the dye concentration. Increasing the concentration of the dye increases the spectral intensity of the dimers, and increasing the pump energy produces major radiative and non-radiative energy transfers from monomers to dimers. If the pump energy is at a very low level, regardless of the dye concentration, the spectra are broadened. Simultaneous laser emissions at desired wavelengths in scattering gain media can be achieved by using a dye mixture.

In the light of the deep analyses of subspace recognition and SIFT recognition, a novel image recognition based on subspace and SIFT is proposed to provide a recognition from global features to minutiae features. First, subspace is used to implement coarse image recognition, gaining one or more candidate samples with different identities. Then, a special SIFT recognition environment is designed, in which the approach takes all the images as objects, builds a multi-object sample image with its size limited below a certain size, detects SIFT points based on object regions and recognizes the test image through SIFT point registration statistical vote. The experiments show that the designed SIFT recognition environment can increase SIFT recognition accuracy and the method based on subspace and SIFT can provide accurate recognitions in a mass of images. Under some special environments, recognition accuracy tends to 100%.

The competition on population inversion between two lasing modes in one-dimensional (1D) active random media is investigated by simultaneously solving Maxwell's equations and rate equations of electronic population. Results indicated that the increasing of concentration of the dye increase the spectral intensity of the dimer and the increase of the pump energy produces a major radiative and non-radiative energy transfers from monomers to dimers. The simulations of the new monomerdimer laser model agree very well with the experimental datas and promote the development of random lasing in the mixed dye media.

The pulsing random lasing from random media is investigated by solving Maxwell’s equations based on a dispersive model Results indicate that although the dispersion in optical domain is relatively small, the random lasing depends strongly on the pumping process pumped by femtosecond-lasing pulses.

To make image segmentation accord with user's inclinations, semi-supervised clustering image segmentation is used. It applies manual guides and pays more attention to user's preferences. Watershed is adopted to segment image into series of small regions, which are basic units for segmentation. In the method, adjacent or nearby regions for labeled regions are assumed to belong to the same cluster. Labeled data and unlabeled data are gotten based on manual guides and assigned different weights during iterative processes. A penalty function is introduced when labeled data are incorrectly segmented. For a complex object to be segmented, its different parts are first segmented independently, and the outputs are merged finally. The experimental results show that region-based semi-supervised clustering image segmentation is fast and precise, and its classification results are more in line with user's requirements.

Different from the conventional lasers, the multiple scattering provides positive feedback in the disordered media. So the research on the relationship between the scatters and the modes exist in two-dimensional disordered media is very significant. The special randomness of scatterers is the main factor to yield the localization of light-waves in the disordered media when the scatterers are isotropic. If the scatterers are made of anisotropic material such as uniaxial crystal, ordered scatterers can also form localization of light-waves if the index of refraction of the uniaxial scatterers distribute randomly in two dimensional media. The randomness of the rotation angle of the optic axis determines the index of refraction of each scattering particle. The threshold property of two-dimensional random media with uniaxial scatterers investigated by simultaneously solving Maxwell's equations and rate equations of electronic population for transverse electric (TE) modes. Results show that the lasing threshold of two-dimensional media direct ratio to the degree of the randomness of the distribution of scatterers including both spatial position and index of refraction. The degree of randomness can be described by a parameter.

Two lasing modes are observed in highly scattering media pumped by 532nm laser pulses. The competition between two modes is investigated by simultaneously solving a new numerical model. Results indicated that the dominating lasing mode is determined by both concentration of laser dye and scattering particle density. And the mode has an obvious shift with the increase of density of scattering particles. The simulations of the new laser model agree very well with the experimental data.

This paper modified the structure of the original PSO algorithm. It proposes that the particles' position have relationship with the one particle's and the whole swarm's perceive extent in the processing of this time and last time, and presents the inertial weight based on simulated annealing temperature. So a new Particle Swarm Optimization algorithm (NPSO) is proposed. It can not improve the one particle's and the whole swarm's perceivable extent and improve the searching efficient but also increase variety of particles and overcome the defect of sinking the local optimal efficiently. At the same time we give the convergence condition of this new algorithm. The algorithm of PSO and NPSO and LPSO are tested with four well-known benchmark functions. The experiments show that the convergence speed of NPSO is significantly superior to PSO and LPSO. The convergence accuracy is increased.

Detecting incidents on urban freeway or arterials using loop detector data is quite challenging. Considering the ability of fuzzy clustering for data discretization, that of rough sets theory to reduction of decision system, and that of fuzzy neural networks to nonlinear mapping, a novel hybrid neuron-fuzzy inference method that synergies fuzzy c-means (FCM),rough sets theory, and adaptive neuro-fuzzy inference system for incident detection was proposed. Firstly, the continuous attributes from detector loop were discretized with FCM clustering. Then, attribute reduction were performed based on rough sets theory using generic algorithm, and the key conditions for incident were determined. Lastly, according to the chosen attribute data, the ANFIS(Adaptive-Network-Based Fuzzy Inference System) was designed for detection. The major advantage of this approach is to optimize the overall structure of ANFIS and avoid the "dimensional disaster" with rough sets theory to attribute reduction. The efficiency of the new method is also illustrated by means of applying to real traffic data, the result of the experiment demonstrated that the solution was very effective to increase the recognition rate and to reduce the number of false detections.

This paper presents a new adaptive particle swarm optimization algorithm with genetic mutation operator. In the algorithm, we give a new adaptive inertia weight to access to local search quickly at the front of the iteration and use the adaptive variance and immune algorithm new affinity definition of the swarm to judge whether the algorithm sink into local minimum or not, then we use a new genetic mutation operator for some particles to escape from the local minimum's basin of attraction and realize global search. The experiments on six problems show that the modified PSO algorithm can improve the global search ability and greatly enhance the successful rate of search.

The dual-color laser action from the Rh6G solution with TiO2 scattering particles is investigated by solving Maxwell’s equations and rate equations of electronic population simultaneously. A one-dimensional (1D) dispersive model is proposed to explain the experiment results. The results indicate that, although the dispersion in optical domain is relatively small, the dispersion for both gain materials and scattering particles has significant influence on modes of random lasing, which lead to more lasing modes and lower spectral intensity.