Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms

A-units active actual analysis appears applied approach assigned association assumed bars becomes binomial bounded brain Chapter classification complex components 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 increase indicate inhibitory initial input interest layer learning limit means mechanisms memory negative neurons Note object obtained occur organization origin output particular patterns perceptron performance positive possible present probability problem properties random recognition reinforcement relations remains represented response retina seen selected sensory sequence shown shows signal similarity simple solution specific square stimuli studies sufficient tend terminal theorem threshold transformation transmission units variable vector yield zero