Analysis of signals by means of mathematical transformations proved to be an effective method in various aspects, such as filtering, system identification, feature extraction, classification etc. The most widely used method in transform-domain techniques operates with fixed basic functions like the trigonometric functions in the Fourier transform, Walsh functions in the Walsh–Fourier...
Our research focuses on the suitability of universal model explanatory tools and methods for qualitative abstractions of embedded AI models for V&V purposes.
The rapidly spreading solutions based on embedded artificial intelligence in cyber-physical systems have defined the behavioral model of complex systems with machine learning tools. A fundamental obstacle to their prevalence is that...
In complex systems, the importance of empirical data analysis-based testing, verification, and validation increases to assure a proper level of service under the typically varying workload. Scaling of these systems needs reusable and scale-independent models for reconfigurability.
The limited faithfulness of speculative analytic models does not support complex system identification. This way,...
