|
|
|
|
|
Nan Xu, Zhiming Zhang and Yongming Liu
Structural Health Monitoring requires the continuous assessment of a structure?s operational conditions, which involves the collection and analysis of a large amount of data in both spatial and temporal domains. Conventionally, both data-driven and physi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Qingcheng Fan, Sicong Liu, Chunjiang Zhao and Shuqin Li
Feature selection is crucial in classification tasks as it helps to extract relevant information while reducing redundancy. This paper presents a novel method that considers both instance and label correlation. By employing the least squares method, we c...
ver más
|
|
|
|
|
|
|
|
|
|
|
Cong Wang, Liyue Wang, Chen Cao, Gang Sun, Yufeng Huang and Sili Zhou
As a core component of an aero-engine, the aerodynamic performance of the nacelle is essential for the overall performance of an aircraft. However, the direct design of a three-dimensional (3D) nacelle is limited by the complex design space consisting of...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rito Clifford Maswanganyi, Chungling Tu, Pius Adewale Owolawi and Shengzhi Du
Transfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used to address the challenges of cross-session ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Peng Chen and Huibing Wang
Semi-supervised metric learning intends to learn a distance function from the limited labeled data as well as a large amount of unlabeled data to better gauge the similarities of any two instances than using a general distance function. However, most exi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yi Zhang, Jie Ma, Xiaolin Qin, Yongming Li and Zuwei Zhang
Chronic diseases are severe and life-threatening, and their accurate early diagnosis is difficult. Machine-learning-based processes of data collected from the human body using wearable sensors are a valid method currently usable for diagnosis. However, i...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yuwen Fu, E. Xia, Duan Huang and Yumei Jing
Machine learning has been applied in continuous-variable quantum key distribution (CVQKD) systems to address the growing threat of quantum hacking attacks. However, the use of machine learning algorithms for detecting these attacks has uncovered a vulner...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rui-Yu Li, Yu Guo and Bin Zhang
Nonnegative matrix factorization (NMF) is an efficient method for feature learning in the field of machine learning and data mining. To investigate the nonlinear characteristics of datasets, kernel-method-based NMF (KNMF) and its graph-regularized extens...
ver más
|
|
|
|
|
|
|
|
|
|
|
Saidur R. Pavel and Yimin D. Zhang
Massive multiple-input multiple-output (MIMO) technology, which is characterized by the use of a large number of antennas, is a key enabler for the next-generation wireless communication and beyond. Despite its potential for high performance, implementin...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tulsi Patel, Mark W. Jones and Thomas Redfern
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders...
ver más
|
|
|
|
|
|