A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such

Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems f

Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear sys