An intelligent system is one that shows characteristics including, but not restricted to, learning, adaptation, and problem-solving. Artificial Neural Network (ANN) Systems are intelligent systems designed on the foundation of statistical models of learning that mimic biological system like the human central nervous system. Such ANN systems represent the theme of this ebook. This ebook also explains concepts related to evolutionary methods, clustering algorithms, and others networks that are complementary to ANN system.
The ebook is divided into two parts. The first part describes basic concepts derived from the natural biological neuron and introduces only scientific frameworks used to develop a feasible ANN model. The second part encompasses the design, analysis, performance assessment, and testing of ANN models. Concepts like Bayesian networks, multi-classifiers, and neuromorphic ANN systems are explained, among others.
Artificial Neural Systems: Principles and Practice, (PDF) takes a developmental perspective on the subject of ANN systems, making it a helpful resource for students undertaking graduate courses and research projects, and working professionals (software developers, engineers) in the field of intelligent systems design.
NOTE: The product only includes the ebook, Artificial Neural Systems: Principles and Practice in PDF. No access codes are included.
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