Principles of neurodynamics: perceptrons and the theory of brain mechanisms

A-set A-units responding active analysis analyzed assumed behavior bias binomial model biological brain model Cerebral Cortex Chapter components configuration considered Cornell Aeronautical Laboratory cross-coupled perceptrons cross-coupled systems detectors distribution elementary perceptron employed environment equal equation error correction procedure excitatory expected value Figure finite four-layer given inhibitory connections input connections input signal intersection layer learning matrix mechanisms memory negative class neurons normal distribution obtained occur organization orthant output parameters patterns perception performance phase space phoneme Poisson model positive class possible preconditioning sequence probability problem properties random random variable reinforcement response function retina retinal field S-controlled Section sensory sensory unit set of A-units similarity simple perceptron solution exists specific stimuli stimulus sequences stimulus world tend terminal test stimulus theorem three-layer threshold training sequence transformation transformation group transmission function unbounded system units variable vector Venn diagram vertical bars visual y-system zero