Perceptron Function

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A Perceptron Function is a linear classification function composed of a parameterized weighted sum and an activation function.





  • (Kanal, 2003) ⇒ Laveen N. Kanal. (2003). “Perceptron.” In: "Encyclopedia of Computer Science, 4th edition.” John Wiley and Sons. ISSN:0-470-86412-5
    • QUOTE: In 1957 the psychologist Frank Rosenblatt proposed "The Perceptron: a perceiving and recognizing automaton" as a class of artificial nerve nets, embodying aspects of the brain and receptors of biological systems. Fig. 1 shows the network of the Mark 1 Perceptron. Later, Rosenblatt protested that the term perceptron, originally intended as a generic name for a variety of theoretical nerve nets, was actually associated with a very specific piece of hardware (Rosenblatt, 1962). The basic building block of a perceptron is an element that accepts a number of inputs xi, i = 1,..., N, and computes a weighted sum of these inputs where, for each input, its fixed weight ω can be only + 1 or - 1. The sum is then compared with a threshold θ, and an output y is produced that is either 0 or 1, depending on whether or not the sum exceeds the threshold. In other words …

      … A perceptron is a signal transmission network consisting of sensory units (S units), association units (A units), and output or response units (R units). The receptor of the perceptron is analogous to the retina of the eye and is made of an array of sensory elements (photocells). Depending on whether or not an S-unit is excited, it produces a binary output. A randomly selected set of retinal cells is connected to the next level of the network, the A units. Each A unit behaves like the basic building block discussed abowvhee, re the + 1, - 1 weights for the inputs to each A unit are randomly assigned. The threshold for all A units is the same.




  • (Novikoff, 1962) ⇒ A. B. Novikoff. (1962). “On Convergence Proofs on Perceptrons. Symposium on the Mathematical Theory of Automata, 12.


  • (Rosenblatt, 1958) ⇒ Frank Rosenblatt. (1958). “The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain.” Psychological Review, 65(6).