Biomedical systems are characterized by high complexity and nonlinear dynamics, having fractal and multifractal nature exhibiting even chaotic behavior. This is expressed particularly, but not exclusively, in different vital signs, brain networks, and neuronal and cardiac activities. New measurement techniques and sensing devices of latest generation enable deeper insight into subtle and complex mechanism of biomedical processes. Unfortunately, biomedical data generate extremely large series, producing difficult technical problems concerning the analysis or processing of such data. Managing, processing, storing, retrieving, and transferring such data are challenging issues and need development of new methods and algorithms that could be implemented in different phases of biomedical data analysis or data mining. Besides the linear processing methods, the nonlinear ones including fractal and multifractal analyses, as well as usage of artificial intelligence methods, take place in analyzing complex biomedical signals. It is expected that combination of nonlinear and linear methods could give us better insight into the nature of these data leading towards the more appropriate solutions to analysis of complex data.

We invite authors to submit original research articles as well as review articles that will illustrate and stimulate the continuing efforts in developing the new methods, algorithms, and tools for modeling, processing, and analyzing complex biomedical signals.

Potential topics include but are not limited to the following:

• Biomedical system modeling
• Methods for visualization of biomedical processes
• Biomedical signal understanding and description
• Linear methods for biomedical signal processing
• Nonlinear methods for biomedical signal processing
• Neural network signal processing
• Biomedical data classification
• Biomedical data mining
• Decision support systems applied to different biomedical signals
• Fuzzy inference