Neural Network Modeling

Offers an approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. This work helps to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics.
Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.