Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book
This book is devoted to the theory of mathematical model building, using experimental data. There are many situations where accurate mathematical models of real systems are desirable. For example
missing details of LPV system theory that have hindered the formulation of a well established identification framework. By proposing a unified LPV system theory, based on a behavioral approach, the concepts
a thorough understanding of how some core low-level building blocks of a multi-biometric system are implemented. While this book covers a range of biometric traits including facial geometry, 3D ear form
in all fields.
Some of the areas we publish in:
-Databases and information systems
planning. New techniques in signal processing, adaptive control, non-linear system identification, multi-agent simulation, eigenvalue analysis, risk assessment, modeling of dynamic systems, finite difference
Product Description: In today's security-conscious society, real-world applications for authentication or identification require a highly accurate system for recognizing individual humans
Methods of recursive identification deal with the problem of building mathematical models of signals and systems on-line, at the same time as data is being collected. Such methods, which are also
variety of implementations.
A very practical approach for system identification techniques Using Laguerre Models with an appropriated mathematical support