Results 71 to 80 of about 3,257 (211)
Imagined Chinese Speech Decoding Based on Initials and Finals From EEG Activity
IET Signal Processing, Volume 2026, Issue 1, 2026.Brain‐computer interface (BCI) plays an important role in various fields, such as neuroscience, rehabilitation, and machine learning. The silent BCI, which can reconstruct inner speech from neural activity, holds great promise for aphasia patients. In this paper, we design an imagined Chinese speech experimental paradigm based on initials and finals ...
Jingyu Gu +4 more
wiley +1 more source
, 2004 核主元分析(KPCA)是最近出现的一种颇具前景的处理非线性系统问题的有效方法。该方法可通过集成算子与非线性核函数有效计算高维特性空间的主元成分,与线性PCA相比,显示出更高的过程监视性能。本文以一个三维非线性系统为对象,在MATLAB仿真环境下分别进行PCA和KPCA监视仿真 ...
樊立萍, 袁德成, 于海斌, 徐阳
core
Conventional KPCA Approach Applied to Detect Simulated Faults in PV Systems Using Simulated Data
International Journal of PhotoenergyPhotovoltaic (PV) installations have become integral for harnessing solar energy, yet ensuring uninterrupted power generation remains crucial. This study addresses the challenge of maintaining reliability in PV systems by proposing a method to detect and
Charlène Bernadette Lema +4 more
doaj +1 more source
A Physics‐Constrained Adaptive Coupling Framework for Plateau Highway Load Forecasting
IET Smart Grid, Volume 9, Issue 1, January/December 2026.This paper proposes a physics‐informed hybrid framework for short‐term load forecasting in plateau highway microgrids, addressing challenges from nonlinearity, non‐stationarity and spatiotemporal heterogeneity. The approach integrates a sample entropy‐altitude weighted K‐means clustering method with an altitude‐adaptive kernel principal component ...
Ruyan Liu +6 more
wiley +1 more source
Bearing fault diagnosis based on EMD-KPCA and ELM [PDF]
, 2014 In recent years, many studies have been conducted in bearing fault diagnosis, which has attracted increasing attention due to its nonlinear and non-stationary characteristics.
Hang Yuan, Zihan Chen
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Gene- or region-based association study via kernel principal component analysis
BMC Genetics, 2011 Background In genetic association study, especially in GWAS, gene- or region-based methods have been more popular to detect the association between multiple SNPs and diseases (or traits).
Zhao Jinghua +5 more
doaj +1 more source
Exploring the Power of Machine Learning in Analysing Protein–Protein Sequences
IET Systems Biology, Volume 20, Issue 1, January/December 2026.Figure 2 depicts the structure of a peptide bond formed between amino acids to form a polypeptide chain. ABSTRACT Proteins are fundamental biological macromolecules responsible for regulating nearly all cellular processes, and their functions are largely determined by the underlying amino acid sequences.
Anindya Nag +8 more
wiley +1 more source
Fault diagnosis method of train control RBC system based on KPCA-SOM network
Journal of Measurement Science and Instrumentation, 2020 Radio block center（RBC） system is the core equipment of China train control system-3（CTCS-3）. Now, the fault analysis of RBC system mainly depends on manual work, and the diagnostic results are inaccurate and inefficient. Therefore, the intelligent fault
LI Yang-qing, LIN Hai-xiang
doaj
The Journal of Engineering, Volume 2026, Issue 1, January/December 2026.This study proposes a digital twin‐enabled hybrid deep learning approach for tool wear monitoring in CNC milling. A four‐layer digital twin architecture is established to enable bidirectional real‐time interaction between the physical machine and its virtual model.
Shuo Wang +3 more
wiley +1 more source
An Improved KPCA Method of Fault Detection Based on Wavelet Denoising
, 2011 For complicated nonlinear systems, the data inevitably have noise, random disturbance, Traditional kernel principal component analysis (KPCA) methods are very difficult to calculate the kernel matrix K for fault detection with large sample sets.
Zhan Ming Li, Xiao Qiang Zhao
core +1 more source