Engineering Neural Networks

This is the midpoint of the book, placed before the artificial neural network theory and the application section. It contextualizes neural networks to integrate them into a system and understand how a mathematical approach can regulate a system. System engineering methodologies are used to create better, cheaper, more capable products, while AI techniques are used to manage the systems engineering effort. The system engineering approach allows us to evaluate the complexity and the architecture of a system by understanding its elements and the way they are interconnected. In general, a complex system is defined as a series of elements that work together toward a common goal, or a variety of interacting parts that collectively perform a specific function. The term complex clarifies that the elements of the system, initially, have no relevance to each other. Nevertheless, through logical and interactive connections, they become necessary to achieve a predetermined objective The aim of these disciplines is to help a professional to extricate themselves in complex realities. In general, the AI can be used to manage complex systems and to find optimal points between its elements, and must be embedded in the system processes to achieve the right effectiveness.