- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - Shenzhen, China (2018.7.13-2018.7.15)] 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - Robust Nonnegative Local Coordinate Factorization for Hyperspectral Unmixing
摘要： Recently, nonnegative matrix factorization (NMF) has become increasingly popular for hyperspectral unmixing (HU). Due to the non-convex nature of the NMF theory, which is sensitive to the initial value and various noise. To obtain more accurate and robust unmixing model, in this paper, we propose a novel method called robust nonnegative local coordinate factorization (RNLCF). RNLCF adds a local coordinate constraint into the composite loss function which combing classic and Correntropy Induced Metric NMF function. To solve RNLCF, we developed a multiplicative update rules. Experimental results on synthetic and real-world data verify the effectiveness of RNLCF comparing with the representative methods.
关键词： local coordinate,Correntropy Induced Metric,hyperspectral unmixing (HU),nonnegative matrix factorization (NMF)
更新于2025-09-23 15:22:29
-
[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Matching Pursuit Based on Kernel Non-Second Order Minimization
摘要： The orthogonal matching pursuit (OMP) is an important sparse approximation algorithm to recover sparse signals from compressed measurements. However, most MP algorithms are based on the mean square error (MSE) to minimize the recovery error, which is suboptimal when there are outliers. In this paper, we present a new robust OMP algorithm based on kernel non-second order statistics (KNS-OMP), which not only takes advantages of the outlier resistance ability of correntropy but also further extends the second order statistics based correntropy to a non-second order similarity measurement to improve its robustness. The resulted framework is more accurate than the second order ones in reducing the effect of outliers. Experimental results on synthetic and real data show that the proposed method achieves better performances compared with existing methods.
关键词： kernel non-second order measurement,correntropy,sparse recovery,Orthogonal matching pursuit
更新于2025-09-11 14:15:04
-
[IEEE 2017 14th IEEE India Council International Conference (INDICON) - Roorkee (2017.12.15-2017.12.17)] 2017 14th IEEE India Council International Conference (INDICON) - A Correntropy Based Control Algorithm for a Single-Phase Double Stage Grid Integrated Solar PV System
摘要： This paper presents the implementation of a double stage solar photovoltaic (PV) single phase grid connected system using correntropy based control algorithm. This algorithm helps to obtain sinusoidal grid currents even in the presence of nonlinear loads connected at PCC (Point Of Common Coupling), thus improving the power quality of the system. It has almost no steady state error as well as strong filtering ability. The proposed system is configured using a solar PV array, a single phase grid, a voltage source converter (VSC), a DC link capacitor, a boost converter, a ripple filter, an interfacing inductor and the nonlinear loads. The boost converter extracts maximum power from the solar PV array using the drift free MPPT (Maximum Power Point Tracking) method. A prototype is developed to affirm the system performance by testing it under various conditions. The grid conditions of the system obtained after the application of this control strategy conforms well to the harmonic standard IEEE 519.
关键词： Correntropy,MPPT,power quality,VSC,solar PV array
更新于2025-09-10 09:29:36