Challenges and Applications of Graph Signal Processing
Keywords:Graph Signal Processing, Data training, Sensor networks, Biological Networks, Image and 3-D Point Cloud Processing
It is a well-known fact that the world is developing rapidly, and a lot of development is made towards the betterment and to provide ease to human beings. Recently, a lot of research has been made on the latest signal processing to overcome the deficiencies that were part of classical signals processing. The new term of signal processing under discussion is called Graph Signal Processing (GSP). The essential purpose is to develop the equipment or the advanced devices that could analyze the data characterized on the irregular graphical domains. Here in this paper, the primary goal is to study and examine the essential concepts and the basic ingredients whose basis knowledge is compulsory while looking the Graph signal processing. After that, their linkups are discussed, or their association with the traditional digital signal processing along with the discussion of the basic concepts, which would focus on the ways that are recently being utilized to develop the graph signal processing toolbox. After that, the state-of-the-art topics are discussed, describing the challenges or barriers that occur while working on graph signal processing. Then, in the end, different applications are analyzed using the graph signal processing technique.