## Two theorems of statistical separability in the perceptron (Project Para). |

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### Contents

THE IMPORTANCE OF PERCEPTUAL PROCESSES FOR AUTOMATA | 3 |

THE CONTINUOUS TRANSDUCER NEURON | 6 |

ORGANIZATION OF A PERCEPTRON | 9 |

5 other sections not shown

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### Common terms and phrases

amplitude analysis arbitrary environment arbitrary stimulus association cell association system assumed binary response biological Boolean algebra central nervous system Class C perceptron Class C system Class C theorem classes of forms classes of stimuli clear column sums components concept Consequently consider continuous transducer neuron continuous transducer perceptron Cornell Aeronautical Laboratory corollary correlation coefficients corresponds covariance decay diagonal terminal diagonally symmetric difference digital computer distributions of origin elements equation 16 error probability evoke the response expected value feedback signal Figure frequency growth function homeostat human brain increase indicated inhibitory input signal magnitude Markovian Markovian process mathematics matrix measure the similarity negative Neumann neutral number of A-units opposite class order to prove origin points output signals positive proportional reinforcement operator RESPONSE UNITS retina saturated sensory sensory system shown spontaneous organization statistical separability stimulus classes stimulus of Class strongly trapping system will tend terminal condition theory of statistical zero