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ITS PSDM develops mathematical research and its application in the leading fields of ITS. The development of mathematical research in ITS PSDM is explained in the following fishbone research
Research in the field of analysis is emphasized on developing theories about functional analysis and wavelet analysis along with their application:
Research on algebra is emphasized on the development of theories in the fields of algebra itself and several other related fields. Research topics on algebra are emphasized in several fields, namely:
Data assimilation is actually an applied field of mathematics based on the fields of analysis and algebra. Data assimilation research emphasizes the development of data assimilation methods which are then applied to various fields to analyze the reliability of the development of the method.
Data assimilation research is supported by capabilities
Some research topics that can be taken include
Biomathematics
Research in the field of control methods emphasizes the development of methods based on mathematical theories such as Linear Algebra and Matrix, Differential Equations and Systems theory. Linear algebra and matrix are supported by knowledge of matrix convolution transformations and eigen values. Differential equations cover ordinary differential equations, partial differential equations and also numerical differential equations. System theory includes linear and nonlinear systems, deterministic and stochastic systems and descriptor systems. While research that can be developed in the control method / design is
Bioinformatics
Data mining is a branch of studies in computer science, mathematics, and statistics that have developed very rapidly in the last few decades. Data Mining is a term used to find new patterns (knowledge) in a large amount of data. Data mining uses mathematical methods, statistics, artificial intelligence and machine learning to extract and identify useful information and related knowledge from various sources of Big Data. It could also be said that data mining is a process to find meaningful relationships, patterns and tendencies by examining from a group of Big Data stored in storage media using methods that can be used for data pattern recognition.
Some methods in Mathematics developed into tools in data mining include fuzzy sets, rough sets, partial orders, graphs, hypergraf, size theory, probability and stochastic theories, artificial neural networks, and others.
Various applications that have been developed in research in the Department of Mathematics include:
Research in the field of computational mathematics is emphasized in the analysis and development of algorithms and digital image processing methods and also the application of image processing on several real problems. In order to develop algorithms and image processing methods requires basic knowledge of mathematics, namely: