Single-Layer ANN Training System

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A Single-Layer ANN Training System is a ANN Training System that implements a Single-Layer ANN Training Algorithm to solve a Single-Layer ANN Training Task.







  • (Rosenblatt, 1957) ⇒ Rosenblatt,m F. (1957). "The perceptron, a perceiving and recognizing automaton (Project Para)". Cornell Aeronautical Laboratory.
    • PREFACE: The work described in this report was supported as a part of the internal research program of the Cornell Aeronautical Laboratory, Inc. The concepts discussed had their origins in some independent research by the author in the field of physiological psychology, in which the aim has been to formulate a brain analogue useful in analysis. This area of research has been of active interest to the author for five or six years. The perceptron concept is a recent product of this research program; the current effort is aimed at establishing the technical and economic feasibility of the perceptron.


  • (McCulloch & Pitts, 1943) ⇒ McCulloch, W. S., & Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity. The bulletin of mathematical biophysics, 5(4), 115-133.
    • ABSTRACT: Because of the “all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior of every net can be described in these terms, with the addition of more complicated logical means for nets containing circles; and that for any logical expression satisfying certain conditions, one can find a net behaving in the fashion it describes. It is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under the other and gives the same results, although perhaps not in the same time. Various applications of the calculus are discussed.