Mental workload refers to the cognitive effort required to perform tasks, and it is an important
factor in various fields, including system design, clinical medicine, and industrial …

Feature selection (FS) plays an important role in data mining and recognition, especially
regarding large scale text, images and biological data. The Markov blanket provides a …

High-dimensional small sample data are prone to the curse of dimensionality and overfitting
and contain many irrelevant and redundant features. In order to solve these feature selection …

Abstract System identification has been applied in diverse areas over past decades. In
particular, parametric modelling approaches such as linear and nonlinear autoregressive …

In efforts to discover disease mechanisms and improve clinical diagnosis of tumors, it is
useful to mine profiles for informative genes with definite biological meanings and to build …

Feature selection or attribute reduction is an important data preprocessing technique for
dimensionality reduction in machine learning and data mining. In this paper, a novel feature …

Background Identification of differentially expressed genes, ie, genes whose transcript
abundance level differs across different biological or physiological conditions, was indeed a …

The basic experimental data of traditional Chinese medicine are generally obtained by high‐
performance liquid chromatography and mass spectrometry. The data often show the …

A prerequisite to understand neuronal function and characteristic is to classify neuron
correctly. The existing classification techniques are usually based on structural characteristic …

This thesis provides an investigation of environmental systems modelling and analysis
based on system identification techniques. In particular, this work focuses on adapting and …