摘要稀疏表示模型常利用训练样本学习过完备字典, 旨在获得信号的冗余稀疏表示. 设计简单,
高效, 通用性强的字典学习算法是目前的主要研究方向之一, 也是信息领域的研究热点 …

Objective: Improve the reconstructed image with fast and multiclass dictionaries learning
when magnetic resonance imaging is accelerated by undersampling the k-space data …

In complex operating conditions, the monitoring signals of mechanical equipment are
susceptible to interference from multiple vibration sources and environmental noise …

This book revolves around the question of designing a matrix D∈ Rm× n called dictionary,
such that to obtain good sparse representations y≈ Dx for a class of signals y∈ Rm given …

In recent years, sparse signal modeling, especially using the synthesis model has been
popular. Sparse coding in the synthesis model is however, NP-hard. Recently, interest has …

The high-fidelity extraction of the nonperiodic fault transients of rolling bearings under
variable speed is of significant importance, while still a challenge for early-stage fault …

Dictionary learning, which is based on sparse coding, has been frequently applied to many
tasks related to remote sensing processes. Recently, many new non-analytic dictionary …

The noise produced by the inspiral of millions of white dwarf binaries in the Milky Way may
pose a threat to one of the main goals of the space-based LISA mission: the detection of …

Multi-label text classification is a challenging task in many real applications. Mostly, in all the
traditional techniques, word2vec is used to show the sequential information among text …

Visual query of spatiotemporal data is becoming an increasingly important function in visual
analytics applications. Various works have been presented for querying large …