The book is divided into two parts. The first part explains basic concepts derived from the natural biological neuron and introduces purely scientific frameworks used to develop a viable ANN model. The second part expands over to the design analysis performance assessment and testing of ANN models. Concepts such as Bayesian networks multi-classifiers and neuromorphic ANN systems are explained among others.
Artificial Neural Systems: Principles and Practice takes a developmental perspective on the subject of ANN systems making it a beneficial resource for students undertaking graduate courses and research projects and working professionals (engineers software developers) in the field of intelligent systems design.
Loading...
Loading...
