Overview and comparative study of dimensionality reduction techniques for high dimensional data
S Ayesha, MK Hanif, R Talib - Information Fusion, 2020 - Elsevier
The recent developments in the modern data collection tools, techniques, and storage
capabilities are leading towards huge volume of data. The dimensions of data indicate the …
capabilities are leading towards huge volume of data. The dimensions of data indicate the …
[HTML][HTML] Review of dimension reduction methods
Purpose: This study sought to review the characteristics, strengths, weaknesses variants,
applications areas and data types applied on the various Dimension Reduction techniques …
applications areas and data types applied on the various Dimension Reduction techniques …
Real-time embedded EMG signal analysis for wrist-hand pose identification
SA Raurale, J McAllister… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Electromyographic (EMG) signals sensed at the skin surface on the forearm can be used to
accurately infer wrist-hand poses. However this is only possible when the EMG sensors are …
accurately infer wrist-hand poses. However this is only possible when the EMG sensors are …
Graph multiview canonical correlation analysis
Multiview canonical correlation analysis (MCCA) seeks latent low-dimensional
representations encountered with multiview data of shared entities (aka common sources) …
representations encountered with multiview data of shared entities (aka common sources) …
Canonical correlation analysis of datasets with a common source graph
Canonical correlation analysis (CCA) is a powerful technique for discovering whether or not
hidden sources are commonly present in two (or more) datasets. Its well-appreciated merits …
hidden sources are commonly present in two (or more) datasets. Its well-appreciated merits …
Vector set classification by signal subspace matching
We present a powerful solution to the problem of vector set classification, based on a novel
goodness-of-fit metric, referred to as signal subspace matching (SSM). Unlike the existing …
goodness-of-fit metric, referred to as signal subspace matching (SSM). Unlike the existing …
Novel fast and automatic condition monitoring strategy based on small amount of labeled data
I Attoui - IEEE Transactions on Systems, Man, and Cybernetics …, 2020 - ieeexplore.ieee.org
Signal-based automatic condition monitoring techniques are one of the effective ways to
ensure the operational safety of modern industrial systems. Currently, the main challenge is …
ensure the operational safety of modern industrial systems. Currently, the main challenge is …
A generalized CUR decomposition for matrix pairs
PY Gidisu, ME Hochstenbach - SIAM Journal on Mathematics of Data Science, 2022 - SIAM
We propose a generalized CUR (GCUR) decomposition for matrix pairs (A,B). Given
matrices A and B with the same number of columns, such a decomposition provides low …
matrices A and B with the same number of columns, such a decomposition provides low …
Deep Contrastive Principal Component Analysis Adaptive to Nonlinear Data
Principal component analysis (PCA) is one of the most fundamental techniques for Big Data
analytics in eg, smart manufacturing and biostatistics, which is capable of extracting the most …
analytics in eg, smart manufacturing and biostatistics, which is capable of extracting the most …
X-MyoNET: Biometric Identification using Deep Processing of Dynamic Surface Electromyography
This article investigates the potential of surface electromyography (sEMG) as a new
biometric modality and proposes a deep neural network architecture as the backbone of a …
biometric modality and proposes a deep neural network architecture as the backbone of a …