scholarly journals Electrocardiograph Identification Using Hybrid Quantization Sparse Matrix and Multi-Dimensional Approaches

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4138
Author(s):  
Kuo-Kun Tseng ◽  
Jiao Lo ◽  
Chih-Cheng Chen ◽  
Shu-Yi Tu ◽  
Cheng-Fu Yang
Keyword(s):  
Matrix Method ◽  
Sparse Matrix ◽  
Human Identification ◽  
Recognition Algorithm ◽  
Blood Oxygen ◽  
Dimensional Approach ◽  
Identification Rate ◽  
Ecg Signals ◽  
Biometric Security ◽  
Biometric Information

Electrocardiograph (ECG) technology is vital for biometric security, and blood oxygen is essential for human survival. In this study, ECG signals and blood oxygen levels are combined to increase the accuracy and efficiency of human identification and verification. The proposed scheme maps the combined biometric information to a matrix and quantifies it as a sparse matrix for reorganizational purposes. Experimental results confirm a much better identification rate than in other ECG-related identification studies. The literature shows no research in human identification using the quantization sparse matrix method with ECG and blood oxygen data combined. We propose a multi-dimensional approach that can improve the accuracy and reduce the complexity of the recognition algorithm.

scholarly journals Sparse Matrix for ECG Identification with Two-Lead Features

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Kuo-Kun Tseng ◽  
Jiao Luo ◽  
Robert Hegarty ◽  
Wenmin Wang ◽  
Dong Haiting
Keyword(s):  
Feature Extraction ◽  
Matrix Method ◽  
Sparse Matrix ◽  
Human Identification ◽  
Two Dimensional ◽  
Ecg Signals ◽  
Biometric Security ◽  
Dimensional Matrix ◽  
The Matrix ◽  
Sparse Matrix Techniques

Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.

An approach for human identification based on time and frequency domain features extracted from ECG signals

2011 ◽  
Author(s):  
Shaikh Anowarul Fattah ◽  
Abu Shafin Mohammad Mahdee Jameel ◽  
Rajib Goswami ◽  
Sudip Kumar Saha ◽  
Nitu Syed ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Human Identification ◽  
Ecg Signals

A sparse matrix method for renal models

1982 ◽  
Vol 61 (2) ◽  
pp. 191-203 ◽  
Author(s):  
R.P. Tewarson ◽  
S. Gupta
Keyword(s):  
Matrix Method ◽  
Sparse Matrix

Human Identification From ECG Signals Via Sparse Representation of Local Segments

2013 ◽  
Vol 20 (10) ◽  
pp. 937-940 ◽  
Author(s):  
Jin Wang ◽  
Mary She ◽  
Saeid Nahavandi ◽  
Abbas Kouzani
Keyword(s):  
Sparse Representation ◽  
Human Identification ◽  
Ecg Signals

Direct Global Stiffness Matrix Method for 3-D Truss Dynamics

1995 ◽  
Author(s):  
J. Robert Fricke ◽  
Mark A. Hayner
Keyword(s):  
Stiffness Matrix ◽  
Matrix Method ◽  
Sparse Matrix ◽  
Broad Band ◽  
Inversion Method ◽  
Design Goal ◽  
Energy Decay Rate ◽  
Matrix Inversion Method ◽  
Applied Forces ◽  
Global Stiffness Matrix

Abstract This paper deals with the acoustical design goal for a new approach in submarine architecture calling for the use of an internal truss to support the ship’s control and living spaces in the forward section. The acoustical design goal is to minimize truss vibration over a broad band of frequency through the application of passive damping treatments. Damping can be placed in three generic locations: 1) in or along the truss members, 2) in the joints between members, and 3) in dynamic absorbers placed at discrete locations along the truss members. This paper develops the framework for evaluating ways to achieve the stated acoustical goal. We outline the formulation of the Direct Global Stiffness Matrix method (DGSM), which is used to relate externally applied forces and moments at truss joints to joint displacements everywhere on the truss. The model is kinematically constrained by matching welded boundary conditions at the joints, and the joint displacements are computed by a sparse matrix inversion method. From these displacements, wave amplitudes for each of the three wave types, longitudinal, torsional, and flexural, may be computed on any of the beam members. An example of the use of this method illustrates the sensitivity of the global energy decay rate to the truss damping parameters, which are the only free parameters of the model. [Work sponsored by ARPA/ONR]

scholarly journals Evaluation of the Transport Matrix Method for simulation of ocean biogeochemical tracers

2017 ◽  
Author(s):  
Karin F. Kvale ◽  
Samar Khatiwala ◽  
Heiner Dietze ◽  
Iris Kriest ◽  
Andreas Oschlies
Keyword(s):  
Matrix Method ◽  
Climate Model ◽  
Sparse Matrix ◽  
Detailed Comparison ◽  
Biogeochemical Model ◽  
Attractive Alternative ◽  
Earth System ◽  
Tracer Transport ◽  
Biogeochemical Models ◽  
Biogeochemical Tracers

Abstract. Conventional integration of earth system and ocean models can accrue considerable computational expenses, particularly for marine biogeochemical applications. Offline numerical schemes in which only the biogeochemical tracers are time-stepped and transported using a pre-computed circulation field can substantially reduce the burden and are thus an attractive alternative. One such scheme is the transport matrix method (TMM), which represents tracer transport as a sequence of sparse matrix-vector products that can be performed efficiently on distributed-memory computers. While the TMM has been used for a variety of geochemical and biogeochemical studies, to date the resulting solutions have not been comprehensively assessed against their online counterparts. Here, we present a detailed comparison of the two. It is based on simulations of the state-of-the-art biogeochemical sub-model embedded within the widely-used University of Victoria Earth System Climate Model (UVic ESCM). Transport matrices were extracted for an equilibrium run of the physical model and subsequently used to integrate the biogeochemical model offline to equilibrium. The identical biogeochemical model was also run online. Our simulations show that offline integration introduces some bias to biogeochemical quantities through the omission of the polar filtering used in UVic ESCM, and in the offline application of time-dependent forcing fields, with high latitudes showing the largest differences with respect to the online model. Differences in other regions and in the seasonality of nutrients and phytoplankton distributions are found to be relatively minor, giving confidence that the TMM is a reliable tool for offline integration of complex biogeochemical models. Moreover, while UVic ESCM is a serial code, the TMM can be run on a parallel machine with no change to the underlying biogeochemical code, thus providing orders of magnitude speed-up over the online model.

Teaching and Examining Sparse Matrix Methods

1995 ◽  
Vol 23 (4) ◽  
pp. 336-342
Author(s):  
F. W. Williams
Keyword(s):  
Matrix Method ◽  
Mental Arithmetic ◽  
Sparse Matrix ◽  
Simultaneous Equations ◽  
Matrix Methods ◽  
The Matrix ◽  
Gauss Elimination ◽  
The Way

A method is presented for concise teaching and examining of the principles and advantages of sparse matrix methods. The method uses only mental arithmetic and is illustrated using Gauss elimination for the solution of simultaneous equations. Indications are given of the ways in which the ideas can be extended to methods other than Gauss elimination and to types of sparse matrix method other than those considered in detail. Indications are also given of how the material can be taught so as to integrate with related matters, such as the evaluation of determinants and the way that the savings obtained by using the most sophisticated sparse matrix methods increase rapidly as the order of the matrix increases.

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