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Qué (quién) es discrete perceptron - definición
ALGORITHM FOR SUPERVISED LEARNING OF BINARY CLASSIFIERS
Threshold neuron; Perceptrons; Linear perceptron; Multiclass perceptron; Perceptron algorithm; Perceptron learning algorithm; Pocket algorithm; McCulloch Pitts neurons
 (20897323365).jpg?width=200 "Camera system of the Mark 1 Perceptron.")
multilayer perceptron
TYPE OF FEEDFORWARD NEURAL NETWORK
Multi-layer perceptron; Multi-layer perceptrons; Vanilla neural network; Multilayer perceptrons; Multi layer perceptron; Applications of multilayer perceptrons
A network composed of more than one layer of neurons, with
some or all of the outputs of each layer connected to one or
more of the inputs of another layer. The first layer is
called the input layer, the last one is the output layer, and
in between there may be one or more hidden layers.
Multilayer perceptron
TYPE OF FEEDFORWARD NEURAL NETWORK
Multi-layer perceptron; Multi-layer perceptrons; Vanilla neural network; Multilayer perceptrons; Multi layer perceptron; Applications of multilayer perceptrons
A multilayer perceptron (MLP) is a fully connected class of feedforward artificial neural network (ANN). The term MLP is used ambiguously, sometimes loosely to mean any feedforward ANN, sometimes strictly to refer to networks composed of multiple layers of perceptrons (with threshold activation); see .
Discrete Laplace operator
ANALOG OF THE CONTINUOUS LAPLACE OPERATO
Discrete Schrödinger operator; Discrete Green's function; Discrete laplace operator; Discrete Schrodinger operator; Discrete Schroedinger operator; Discrete Laplacian operator; Laplace filter
In mathematics, the discrete Laplace operator is an analog of the continuous Laplace operator, defined so that it has meaning on a graph or a discrete grid. For the case of a finite-dimensional graph (having a finite number of edges and vertices), the discrete Laplace operator is more commonly called the Laplacian matrix.
Wikipedia
Perceptron
In machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
