10 papers
A Differential Evolution Algorithm with Neighbor-hood Mutation for DOA Estimation
Bo Zhou, Kaijie Xu, Yinghui Quan +1
Two-dimensional (2D) Multiple Signal Classification algorithm is a powerful technique for high-resolution direction-of-arrival (DOA) estimation in array signal processing. However,…
TransDOA: Calibrating Array Imperfections via Transformer-based Transfer Learning
Bo Zhou, Kaijie Xu, Yinghui Quan +1
In practical scenarios, processes such as sensor design, manufacturing, and installation will introduce certain errors. Furthermore, mutual interference occurs when the sensors rec…
A Novel Fuzzy Bi-Clustering Algorithm with AFS for Identification of Co-Regulated Genes
Kaijie Xu
The identification of co-regulated genes and their transcription-factor binding sites (TFBS) are the key steps toward understanding transcription regulation. In addition to effecti…
Separable symmetric tensors and separable anti-symmetric tensors
Changqing Xu
In this paper, we first introduce the invertibility of even-order tensors and the separable tensors, including separable symmetry tensors and separable anti-symmetry tensors, defin…
An Enhanced Adaptive Bi-clustering Algorithm through Building a Shielding Complex Sub-Matrix
Kaijie Xu
Bi-clustering refers to the task of finding sub-matrices (indexed by a group of columns and a group of rows) within a matrix of data such that the elements of each sub-matrix (data…
Exploiting a Supervised Index for High-accuracy Parameter Estimation in Low SNR
Kaijie Xu
Performance of parameter estimation is one of the most important issues in array signal processing. The root mean square error, probability of success, resolution probabilities, an…
How to Determine an Optimal Noise Subspace?
Kaijie Xu
The Multiple Signal Classification (MUSIC) algorithm based on the orthogonality between the signal subspace and noise subspace is one of the most frequently used method in the esti…
A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes
Kaijie Xu, Witold Pedrycz, Zhiwu Li +2
Traditional clustering methods are limited when dealing with huge and heterogeneous groups of gene expression data, which motivates the development of bi-clustering methods. Bi-clu…
Augmentation of the Reconstruction Performance of Fuzzy C-Means with an Optimized Fuzzification Factor Vector
Kaijie Xu, Witold Pedrycz, Zhiwu Li
Information granules have been considered to be the fundamental constructs of Granular Computing (GrC). As a useful unsupervised learning technique, Fuzzy C-Means (FCM) is one of t…
Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix
Kaijie Xu, Witold Pedrycz, Zhiwu Li +1
As an important technology in artificial intelligence Granular Computing (GrC) has emerged as a new multi-disciplinary paradigm and received much attention in recent years. Informa…