Special issue on fuzzy theoretical model analysis for signal processing

The increasing availability of huge image collections in different application fields, such as medical diagnosis, remote sensing, transmission and encoding, machine/robot vision, and video processing, microscopic imaging has pressed the need, in the last few last years, for the development of efficient techniques capable of managing and processing large collection of image data. Classical signal processing methods often face great difficulties while dealing with images containing noise and distortions. Under such conditions, fuzzy logic methods are effective techniques for the design of a suitable mathematical criterion for matching signal descriptors to detect the correspondences between the signal remains as one of the basic problems of signal matching and computer vision. fuzzy logic techniques turn out to be effective to address challenging real-world signal processing problems that are often characterized by vagueness and uncertainty. This special issue focuses on the innovative fuzzy principles and methods for signal processing. We invite technical articles that have a broad scope and general interest to a signal processing audience. We through call for paper through some conference and research community, we collected more than 326 papers. Based on the peer-review comments, we carefully selected 50 papers for this special issue. Now