Pattern Recognition Comparative Analysis Applied to Fingerprint Indoor Mobile Sensors Localization

2010 ◽  
Author(s):  
Jose Vicente Marti Aviles ◽  
Raul Marin Prades
Keyword(s):  
Pattern Recognition ◽  
Comparative Analysis ◽  
Mobile Sensors

scholarly journals A Systematic Comparative Analysis of Clustering Techniques

2020 ◽  
Vol 25 (2) ◽  
pp. 87-104
Author(s):  
Satinder Bal Gupta ◽  
Rajkumar Yadav ◽  
Shivani Gupta
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Information Retrieval ◽  
Comparative Analysis ◽  
Time Complexity ◽  
Clustering Methods ◽  
Clustering Techniques ◽  
Day By Day

AbstractClustering has now become a very important tool to manage the data in many areas such as pattern recognition, machine learning, information retrieval etc. The database is increasing day by day and thus it is required to maintain the data in such a manner that useful information can easily be extracted and used accordingly. In this process, clustering plays an important role as it forms clusters of the data on the basis of similarity in data. There are more than hundred clustering methods and algorithms that can be used for mining the data but all these algorithms do not provide models for their clusters and thus it becomes difficult to categorise all of them. This paper describes the most commonly used and popular clustering techniques and also compares them on the basis of their merits, demerits and time complexity.

scholarly journals Research on Novel Correlation Coefficient of Neutrosophic Cubic Sets and Its Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Huiling Xue ◽  
Minrong Yu ◽  
Chunfang Chen
Keyword(s):  
Pattern Recognition ◽  
Comparative Analysis ◽  
Correlation Coefficient ◽  
Good Tool ◽  
Decision Method

Single-valued neutrosophic cubic set is a good tool to solve the vague and uncertain problems because it contains more information. The article first gives the correlation coefficient of single-valued neutrosophic cubic sets. Then, a decision method is proposed, and an application in pattern recognition is considered. Finally, examples are given to explain the feasibility of this method. At the same time, the comparative analysis shows the superiority of this method.

A comparative analysis of various EMG pattern recognition methods

1996 ◽  
Vol 18 (5) ◽  
pp. 390-395 ◽  
Author(s):  
W.-J. Kang ◽  
C.-K. Cheng ◽  
J.-S. Lai ◽  
J.-R. Shiu ◽  
T.-S. Kuo
Keyword(s):  
Pattern Recognition ◽  
Comparative Analysis ◽  
Pattern Recognition Methods ◽  
Emg Pattern Recognition

scholarly journals A Comparative Study of Three Resolving Parameters of Graphs

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hafiz Muhammad Ikhlaq ◽  
Hafiz Muhammad Afzal Siddiqui ◽  
Muhammad Imran
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Graph Theory ◽  
Comparative Analysis ◽  
Line Graph ◽  
Metric Dimension ◽  
Chemical Structures ◽  
Digital World ◽  
Diffusion Mechanisms ◽  
Mixed Metric

Graph theory is one of those subjects that is a vital part of the digital world. It is used to monitor the movement of robots on a network, to debug computer networks, to develop algorithms, and to analyze the structural properties of chemical structures, among other things. It is also useful in airplane scheduling and the study of diffusion mechanisms. The parameters computed in this article are very useful in pattern recognition and image processing. A number d f , w = min d w , t , d w , s is referred as distance between f = t s an edge and w a vertex. d w , f 1 ≠ d w , f 2 implies that two edges f 1 , f 2 ∈ E are resolved by node w ∈ V . A set of nodes A is referred to as an edge metric generator if every two links/edges of Γ are resolved by some nodes of A and least cardinality of such sets is termed as edge metric dimension, e dim Γ for a graph Γ . A set B of some nodes of Γ is a mixed metric generator if any two members of V ∪ E are resolved by some members of B . Such a set B with least cardinality is termed as mixed metric dimension, m dim Γ . In this paper, the metric dimension, edge metric dimension, and mixed metric dimension of dragon graph T n , m , line graph of dragon graph L T n , m , paraline graph of dragon graph L S T n , m , and line graph of line graph of dragon graph L L T n , m have been computed. It is shown that these parameters are constant, and a comparative analysis is also given for the said families of graphs.

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