## Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsPart I attempts to review the background, basic sources of data, concepts, and methodology to be employed in the study of perceptrons. In Chapter 2, a brief review of the main alternative approaches to the development of brain models is presented. Chapter 3 considers the physiological and psychological criteria for a suitable model, and attempts to evaluate the empirical evidence which is available on several important issues. Chapter 4 contains basic definitions and some of the notation to be used in later sections are presented. Parts II and III are devoted to a summary of the established theoretical results obtained to date. Part II (Chapters 5 through 14) deals with the theory of three-layer series-coupled perceptrons, on which most work has been done to date. Part III (Chapters 15 through 20) deals with the theory of multi-layer and cross-coupled perceptrons. Part IV is concerned with more speculative models and problems for future analysis. Of necessity, the final chapters become increasingly heuristic in character, as the theory of perceptrons is not yet complete, and new possibilities are continually coming to light. (Author). |

### Common terms and phrases

A-units active actual analysis applied approach assigned association assumed bars becomes bias binomial bounded Chapter classification complex components configuration connections considered consists correction correction procedure corresponding cross-coupled defined DEFINITION depends determine discrimination distribution effect elementary employed environment equal equation error example excitatory exists expected experiments field Figure finite fixed function given horizontal identical increase indicate inhibitory initial input interest intersection layer learning means mechanism memory negative Note object obtained occur organization origin output parameters particular patterns perceptron performance positive possible present probability problem properties random reinforcement relation remain represented response retina S₂ seen selected sensory sequence shown shows signal similarity simple solution specific square stimuli sufficient tend terminal theorem threshold training sequence transformation transmission units variable vector vertical yield zero