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  2. Majority function - Wikipedia

    en.wikipedia.org/wiki/Majority_function

    This is proved using probabilistic method. Thus, this formula is non-constructive. [3] Approaches exist for an explicit formula for majority of polynomial size: Take the median from a sorting network, where each compare-and-swap "wire" is simply an OR gate and an AND gate. The Ajtai–Komlós–Szemerédi (AKS) construction is an example.

  3. Perceptron - Wikipedia

    en.wikipedia.org/wiki/Perceptron

    The Voted Perceptron (Freund and Schapire, 1999), is a variant using multiple weighted perceptrons. The algorithm starts a new perceptron every time an example is wrongly classified, initializing the weights vector with the final weights of the last perceptron.

  4. Triple modular redundancy - Wikipedia

    en.wikipedia.org/wiki/Triple_modular_redundancy

    3-input majority gate using 4 NAND gates. The 3-input majority gate output is 1 if two or more of the inputs of the majority gate are 1; output is 0 if two or more of the majority gate's inputs are 0. Thus, the majority gate is the carry output of a full adder, i.e., the majority gate is a voting machine. [7]

  5. Probabilistic neural network - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_neural_network

    A probabilistic neural network (PNN) [1] is a feedforward neural network, which is widely used in classification and pattern recognition problems.In the PNN algorithm, the parent probability distribution function (PDF) of each class is approximated by a Parzen window and a non-parametric function.

  6. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    [18]: 73–75 Later, in Principles of Neurodynamics (1961), he described "closed-loop cross-coupled" and "back-coupled" perceptron networks, and made theoretical and experimental studies for Hebbian learning in these networks, [17]: Chapter 19, 21 and noted that a fully cross-coupled perceptron network is equivalent to an infinitely deep ...

  7. AND gate - Wikipedia

    en.wikipedia.org/wiki/AND_gate

    The AND gate is a basic digital logic gate that implements the logical conjunction (∧) from mathematical logic – AND gates behave according to their truth table. A HIGH output (1) results only if all the inputs to the AND gate are HIGH (1). If any of the inputs to the AND gate are not HIGH, a LOW (0) is outputted.

  8. Kernel perceptron - Wikipedia

    en.wikipedia.org/wiki/Kernel_perceptron

    The forgetron variant of the kernel perceptron was suggested to deal with this problem. It maintains an active set of examples with non-zero α i, removing ("forgetting") examples from the active set when it exceeds a pre-determined budget and "shrinking" (lowering the weight of) old examples as new ones are promoted to non-zero α i. [5]

  9. And-inverter graph - Wikipedia

    en.wikipedia.org/wiki/And-inverter_graph

    An and-inverter graph (AIG) is a directed, acyclic graph that represents a structural implementation of the logical functionality of a circuit or network.An AIG consists of two-input nodes representing logical conjunction, terminal nodes labeled with variable names, and edges optionally containing markers indicating logical negation.