Graph theory analysis using electroencephalogram (EEG) signals is currently an advanced
technique for seizure prediction. Recent deep learning approaches, which fail to fully …

During the past two decades, epileptic seizure detection and prediction algorithms have
evolved rapidly. However, despite significant performance improvements, their hardware …

This paper comprehensively reviews hardware acceleration techniques and the deployment
of convolutional neural networks (CNNs) for analyzing electroencephalogram (EEG) signals …

This monograph deals with principal component analysis (PCA), kernel component analysis
(KPCA), and independent component analysis (ICA), highlighting their applications to …

Independent Component Analysis (ICA) is a common method exploited in different
biomedical signal processing applications, especially in noise removal of …

This study aims to design and implement a very large scale integration (VLSI) chip of the
extend InfoMax independent component analysis (ICA) algorithm which can separate the …

Blind source separation (BSS) is a problem that appears in many research fields. Fast
Independent components analysis (FastICA) is one of the techniques to solve the problem …

This paper proposes an n-dimensional Simplex FastICA (FICA), an accelerated and low
complex architectural design methodology for FICA to attain high computation speed …

This paper presents a hardware-oriented memory-limited online FastICA algorithm and its
hardware architecture and implementation for eight-channel electroencephalogram (EEG) …

The fastICA method is a popular dimension reduction technique used to reveal patterns in
data. Here we show both theoretically and in practice that the approximations used in …