Manipulating Backward Propagation of Acoustic Waves by a Periodical Structure

In the backward propagation of acoustic waves, the direction of phase velocity is anti-parallel to that of group velocity. We propose a scheme to manipulate the backward propagation using a periodicM structure. The dynamic backward propagation process is further experimentally observed. It is demonstrated that the oblique incident plane wave moves backward when it travels through the periodical structure and the backward shift can be controlled within a certain range.

Propagation Properties of Backward Lamb Waves in Plate Investigated by Dynamic Photoelastic Technique

The dynamic photoelastic technique is employed to visualize and quantify the propagation properties of backward Lamb waves in a plate. Higher energy leakage of second-order symmetric backward wave mode S2b in contrast to third-order anti-symmetric backward mode A3b is shown by the dispersion curve of a plate immersed in water, and then verified by experiments. To avoid the considerable high leakage, the plate is placed in air, both group and phase velocities of modes S2b and A3b in the glass plate are experimentally measured. In comparison with the theoretical values, less than 5% errors are found in experiments.

Auto recognition of carbonate microfacies based on an improved back propagation neural network

Though traditional methods could recognize some facies, e.g. lagoon facies, backshoal facies and foreshoal facies, they couldn't recognize reef facies and shoal facies well. To solve this problem, back propagation neural network(BP-ANN) and an improved BP-ANN with better stability and suitability, optimized by a particle swarm optimizer(PSO) algorithm(PSO-BP-ANN) were proposed to solve the microfacies' auto discrimination of M formation from the R oil field in Iraq. Fourteen wells with complete core, borehole and log data were chosen as the standard wells and 120 microfacies samples were inferred from these 14 wells. Besides, the average value of gamma, neutron and density logs as well as the sum of squares of deviations of gamma were extracted as key parameters to build log facies(facies from log measurements)-microfacies transforming model. The total 120 log facies samples were divided into 12 kinds of log facies and 6 kinds of microfacies, e.g. lagoon bioclasts micrite limestone microfacies, shoal bioclasts grainstone microfacies, backshoal bioclasts packstone microfacies, foreshoal bioclasts micrite limestone microfacies, shallow continental micrite limestone microfacies and reef limestone microfacies. Furthermore, 68 samples of these 120 log facies samples were chosen as training samples and another 52 samples were gotten as testing samples to test the predicting ability of the discrimination template. Compared with conventional methods, like Bayes stepwise discrimination, both the BP-ANN and PSO-BP-ANN can integrate more log details with a correct rate higher than 85%. Furthermore, PSO-BP-ANN has more simple structure, smaller amount of weight and threshold and less iteration time.

Sequential Propagation of Chaos for Mean-Field BSDE Systems

A new class of backward particle systems with sequential interaction is proposed to approximate the mean-field backward stochastic differential equations.It is proven that the weighted empirical measure of this particle system converges to the law of the McKean-Vlasov system as the number of particles grows.Based on the Wasserstein met-ric,quantitative propagation of chaos results are obtained for both linear and quadratic growth conditions.Finally,numerical experiments are conducted to validate our theoretical results.

Construction of Early-warning Model for Plant Diseases and Pests Based on Improved Neural Network

By studying principles and methods related to early-warning model of plant diseases and using PSO method, parameter optimization was conducted to backward propagation neural network, and a pre-warning model for plant diseases based on particle swarm and neural network algorithm was established. The test results showed that the construction of early-warning model is effective and feasible, which will provide a via- ble model structure to establish the effective early-warning platform.

Wireless location algorithm using digital broadcasting signals based on neural network

In order to enhance the accuracy and reliability of wireless location under non-line-of-sight （NLOS） environments,a novel neural network （NN） location approach using the digital broadcasting signals is presented. By the learning ability of the NN and the closely approximate unknown function to any degree of desired accuracy,the input-output mapping relationship between coordinates and the measurement data of time of arrival （TOA） and time difference of arrival （TDOA） is established. A real-time learning algorithm based on the extended Kalman filter （EKF） is used to train the multilayer perceptron （MLP） network by treating the linkweights of a network as the states of the nonlinear dynamic system. Since the EKF-based learning algorithm approximately gives the minimum variance estimate of the linkweights,the convergence is improved in comparison with the backwards error propagation （BP） algorithm. Numerical results illustrate thatthe proposedalgorithmcanachieve enhanced accuracy,and the performance ofthe algorithmis betterthanthat of the BP-based NN algorithm and the least squares （LS） algorithm in the NLOS environments. Moreover,this location method does not depend on a particular distribution of the NLOS error and does not need line-of-sight （ LOS ） or NLOS identification.

Computationally Efficient Nonlinearity Compensation for Coherent Fiber-Optic Systems

Split-step digital backward propagation （DBP） can be combined with coherent detection to compensate for fiber nonlinear impairments. A large number of DBP steps is usually needed for a long-haul fiber system, and this creates a heavy computational load. In a trade-off between complexity and performance, interchannel nonlinearity can be disregarded in order to simplify the DBP algorithm. The number of steps can also be reduced at the expense of performance. In periodic dispersion-managed long-haul transmission systems, optical waveform distortion is dominated by chromatic dispersion. As a result, the nonlinearity of the optical signal repeats in every dispersion period. Because of this periodic behavior, DBP of many fiber spans can be folded into one span. Using this distance-folded DBP method, the required computation for a transoceanic transmission system with full inline dispersion compensation can be reduced by up to two orders of magnitude with negligible penalty. The folded DBP method can be modified to compensate for nonlinearity in fiber links with non-zero residua dispersion per span.

ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS

In the context of tower measured radiation datasets.following the correction principle meeting a diagnostic equation in data quality control and in terms of a technique for model construction on data and ANN(artificial neural network)retrieval for BP correction of radiation measurements with rough errors available,a BP model is presented.Evidence suggests that the developed model works well and is superior to a convenient multivariate linear regression model,indicating its wide applications.

Multi-wavelength erenkov radiations in a microring resonator in combination with two gratings

In this paper,the erenkov radiation of light pulse in a microring and gratings is simulated and investigated.The system design consists of a two-defect grating incorporating a microring,connected with a uniform grating.In simulation,the continuous wave(CW) light pulse with wavelength centered at 1.55 μm is input into the microring device via the two-defect grating.The resonant outputs from the two-defect grating propagate through the microring and uniform grating,where the time delays of those two input pulses with different wavelengths through the system are distinguished by the output uniform grating.From the obtained resonant output pulses,we find that the red-shifted and blue-shifted erenkov pulses are observed.In applications,such a proposed system can be used to form two different optical delay pulses,in which the change in erenkov radiation of them,i.e.,time delay within a microring device system,can be useful for erenkov radiation imaging and sensing applications.