This book addresses the fundamental challenge of constructing accurate continuous-time models from discrete-time sampled data. It is written for researchers and engineers working in control systems, system identification, and signal processing who need to bridge the gap between continuous physical processes and their digital representations. The work focuses on the theoretical underpinnings and practical methodologies for achieving this identification, particularly when dealing with noise and sampling imperfections.

The book is recognized as a specialized technical monograph within the field of system identification. Its focus on continuous-time models derived from sampled data suggests a rigorous, mathematically-oriented approach. The subject matter indicates it is intended for an audience with a strong background in control theory and signal processing, likely academic researchers and advanced engineering practitioners.