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  2. Multilayer perceptron - Wikipedia

    en.wikipedia.org/wiki/Multilayer_perceptron

    If a multilayer perceptron has a linear activation function in all neurons, that is, a linear function that maps the weighted inputs to the output of each neuron, then linear algebra shows that any number of layers can be reduced to a two-layer input-output model.

  3. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Typically, neurons are aggregated into layers. Different layers may perform different transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly passing through multiple intermediate layers (hidden layers). A network is typically called a deep neural network if it has at ...

  4. Types of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Types_of_artificial_neural...

    HTM is a biomimetic model based on memory-prediction theory. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world. HTM combines existing ideas to mimic the neocortex with a simple design that provides many capabilities.

  5. Mark I Perceptron - Wikipedia

    en.wikipedia.org/wiki/Mark_I_Perceptron

    The Mark I Perceptron was organized into three layers: [2] A set of sensory units which receive optical input; A set of association units, each of which fire based on input from multiple sensory units; A set of response units, which fire based on input from multiple association units; The connection between sensory units and association units ...

  6. Perceptron - Wikipedia

    en.wikipedia.org/wiki/Perceptron

    Below is an example of a learning algorithm for a single-layer perceptron with a single output unit. For a single-layer perceptron with multiple output units, since the weights of one output unit are completely separate from all the others', the same algorithm can be run for each output unit.

  7. Feedforward neural network - Wikipedia

    en.wikipedia.org/wiki/Feedforward_neural_network

    The bottom layer of inputs is not always considered a real neural network layer. A multilayer perceptron (MLP) is a misnomer for a modern feedforward artificial neural network, consisting of fully connected neurons (hence the synonym sometimes used of fully connected network (FCN)), often with a nonlinear kind of activation function, organized ...

  8. Frank Rosenblatt - Wikipedia

    en.wikipedia.org/wiki/Frank_Rosenblatt

    The third covers multi-layer and cross-coupled perceptrons, and the fourth back-coupled perceptrons and problems for future study. Rosenblatt used the book to teach an interdisciplinary course entitled "Theory of Brain Mechanisms" that drew students from Cornell's Engineering and Liberal Arts colleges.

  9. Three levels of leadership model - Wikipedia

    en.wikipedia.org/wiki/Three_levels_of_leadership...

    Functional theories: Widely used approaches like Kouzes & Posner's Five Leadership Practices model and Adair's Action-Centered Leadership theory assume that once the leader understands – and has been trained in – the required leadership behaviors, he or she will apply them as needed, regardless of their personality. However, as with the ...