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- 2018
- Conditional Random Fields (CRF)
- Convolutional Neural Network (CNN)
- Fine Classification
- Airborne hyperspectral
- green tide
- Elegant End-to-End Fully Convolutional Network (E3FCN)
- deep learning
- remote sensing
- Moderate Resolution Imaging Spectroradiometer (MODIS)
- Optoelectronic Information Science and Engineering
- Ocean University of China
- Wuhan University
- Central South University
- Hubei University
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Intelligent PV Power System with Unbalanced Current Compensation Using CFNN-AMF
摘要： A novel method is proposed to compensate the three-phase unbalanced currents of power grid under three-phase unbalanced load for a two-stage photovoltaic (PV) power system without the augmentation of active power filter (APF). The PV power system is composed of an interleaved DC/DC converter and a three-level neutral-point clamped (NPC) inverter. Moreover, the PV power system possesses the smart inverter function, in which the output active and reactive powers of the PV inverter are predetermined by a power factor according to grid codes of the utilities. In the proposed method, the dq0-axis compensation currents are obtained through low pass filters (LPFs) to compensate the three-phase unbalanced currents of power grid. Furthermore, in order to improve the control performance of the DC bus voltage of the PV power system under unbalanced load variation condition, an online trained compensatory neural fuzzy network with an asymmetric membership function (CFNN-AMF) is proposed to replace the traditional proportional-integral (PI) controller for the DC bus voltage control. In the proposed CFNN-AMF, the compensatory parameter to integrate pessimistic and optimistic operations of fuzzy systems is embedded in the CFNN. In addition, the dimensions of the Gaussian membership functions are directly extended to AMFs. Additionally, the proposed controllers of the PV power system are implemented by two control platforms using floating-point digital signal processor (DSP). Finally, excellent compensation performance for the three-phase currents of power grid under three-phase unbalanced load can be achieved from the experimental results.
关键词： asymmetric membership function,PV power system,compensatory neural fuzzy network,unbalanced current compensation,three-level neutral-point clamped inverter,interleaved DC/DC converter
更新于2025-09-04 15:30:14
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Algorithm for Processing and Analysis of Raman Spectra using Neural Networks
摘要： The solution of the problem of processing of a large data set when analyzing Raman spectra of a gas mixture is considered. The algorithm is based on the artificial neural network. Conditions for the use of neural networks in solving practical problems of real-time analyzing spectra, including that for remote search for heavy hydrocarbons are determined. The algorithm speed is estimated using computer aids with sequential and parallel data processing.
关键词： data processing,Raman spectra,parallel computing,neural network,software,gas mixture
更新于2025-09-04 15:30:14
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SAR Automatic Target Recognition Using a Roto-Translational Invariant Wavelet-Scattering Convolution Network
摘要： The algorithm of synthetic aperture radar (SAR) for automatic target recognition consists of two stages: feature extraction and classification. The quality of extracted features has significant impacts on the final classification performance. This paper presents a SAR automatic target classification method based on the wavelet-scattering convolution network. By introducing a deep scattering convolution network with complex wavelet filters over spatial and angular variables, robust feature representations can be extracted across various scales and angles without training data. Conventional dimension reduction and a support vector machine classifier are followed to complete the classification task. The proposed method is then tested on the moving and stationary target acquisition and recognition (MSTAR) benchmark data set and achieves an average accuracy of 97.63% on the classification of ten-class targets without data augmentation.
关键词： automatic target classification (ATR),wavelet transform,scattering convolution network,roto-translation invariance,synthetic aperture radar
更新于2025-09-04 15:30:14