Special Issue "Advances in Multidimensional Systems and Signal Processing"

Submission Deadline: 30 October 2020 (closed)
Guest Editors
Prof. Carlos Enrique Montenegro Marin, District University Francisco José de Caldas, Colombia
Prof. Paulo Alonso Gaona Garcia,District University Francisco José de Caldas, Colombia
Prof. Edward Rolando Nuñez Valdez, University of Oviedo, Spain

Summary

A mathematical system having more independent variables and in turn more dimensionality is termed as a multidimensional system. Multidimensional systems are mathematical models dealing with multiple variables which each of which represent individual features of the system. These mathematical models are used to provide solutions to complex problems. In real time environment, most of the available data such as images, audio/signal information, video sequences and associated data are multidimensional (>1D) in nature. Many of the existing mathematical models and control theories are not able to handle and fall short when dealing with 2D state-space models. Multidimensional systems are pivotal in order to stabilize, control, observe and minimize the dimensions of data. Multidimensional systems can able to span statistical and deterministic approaches for modelling, designing, and analyzing discrete and spatiotemporal continuous systems. Multidimensional systems are particularly used in the emerging area of multidimensional signal processing.

 

These systems are fully related to multidimensional data processing, image and signal processing. In earlier days, commercial data were arranged in the form of multidimensional to provide flexibility in data analysis and aid better and faster decision making. The huge volume of raw data was converted into useful information using several computers where business people were deployed to understand and analyze the data. This process is highly complex. Data analysis using multidimensional system is one of the best ways for analyzing the data since it represents a natural, easy and effective way for analyzing the information. Today, a major part of the real-time applications like healthcare big-data analysis, medical image processing, signal processing, satellite image processing, and other geospatial data processing requires a multidimensional system for analyzing the data pertaining to the system and extract useful insights.  

 

Multidimensional signal processing (MSP) is one of the niche branches in signal processing, where it uses multidimensional systems for any signal processing task. Since multidimensional signal processing is a subset of signal processing and unique, it is specifically applied for dealing with data having more than one dimension. If the multidimensional signals and system are separable, then single dimensional signal processing methods can be used. Data sampling is generated from multiple dimensions to process and analyze the multidimensional signals. Image processing, video processing and multisensory radar detection are the best examples for MSP applications. Multidimensional data processing needs highly complex algorithms to handle data transformation because of multiple degrees of freedom. But most of the multidimensional signals and systems are not separable and henceforth multidimensional systems are used for handling multidimensional signals. Multidimensional signal processing is closely related to digital signal processing since it is also used to solve problems using computer modelling and algorithms. Digital image processing is also a sub domain of digital signal processing. Digital images are two dimensional in nature and hence multidimensional systems are used for modelling the same.

 

This special issue on “Advances in Multidimensional Systems and Signal Processing” is focused on inviting original research work carried out towards multidimensional signal processing based on multidimensional systems.

 

The following topics are welcome but not restricted to:

 

• Emerging applications using multidimensional systems.

• Multidimensional system for controlling, predicting, visualizing online medical data.

• Multidimensional filters for multidimensional signal processing.

• Multidimensional system for real-time surveillance video processing.

• Multidimensional control-system for 3D biomedical image processing.

• Multidimensional system for geospatial data processing.

• Advanced discrete mathematical model for multidimensional signal processing.

• Multidimensional system for high dimensional healthcare data processing for predicting diseases online.

• Multidimensional signal processing for human brain signal analysis.

• Spatio-temporal video processing using multidimensional systems.

• Multidimensional system for controlling and stabilization biomedical signals.

• Predicting specific object detection in multidimensional satellite images.

• Multidimensional signal processing using multidimensional control theory on biomedical 3D imaging.

• Multidimensional signal processing by a continuous mathematical model.

• Multidimensional system for human body wearable multisensory data.