In reality, many processes exhibit nonlinear characteristics, and in most cases, they cannot be treated satisfactorily using a linearized approach over a wide operating range. Many nonlinear systems can be modelled and solved using advanced mathematical methods, tools, and techniques from image and signal processing, machine learning, neural networks, pattern recognition, and so on. Developing a systematic approach that leads to efficient and reliable design of nonlinear problems is very beneficial, and it is also a key to analyzing nonlinear systems.
This Special Issue aims to cover new aspects of research in nonlinear systems and their various applications by employing advanced mathematical methods and efficient computational techniques. Original research papers in relevant areas of nonlinear systems are invited, with potential topics including, but not limited to, the following:
- Optimization algorithms in nonlinear problems
- Machine learning in nonlinear problems
- Deep learning in nonlinear problems
- Nonlinear dynamical systems
- Nonlinear differential equations
- Analytical methods
- Approximate numerical solutions
- Complex dynamical networks
- Nonlinear models solving by neural networks
