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input weight vector

См. также в других словарях:

  • Support vector machine — Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. Viewing input data as two sets of vectors in an n dimensional space, an SVM will construct a separating hyperplane in that… …   Wikipedia

  • Synaptic weight — In neuroscience and computer science, synaptic weight refers to the strength or amplitude of a connection between two nodes, corresponding in biology to the amount of influence the firing of one neuron has on another. The term is typically used… …   Wikipedia

  • Self-organizing map — A self organizing map (SOM) is a type of artificial neural network that is trained using unsupervised learning to produce a low dimensional (typically two dimensional), discretized representation of the input space of the training samples, called …   Wikipedia

  • Perceptron — Perceptrons redirects here. For the book of that title, see Perceptrons (book). The perceptron is a type of artificial neural network invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt.[1] It can be seen as the simplest… …   Wikipedia

  • Schönhage-Strassen algorithm — The Schönhage Strassen algorithm is an asymptotically fast multiplication algorithm for large integers. It was developed by Arnold Schönhage and Volker Strassen in 1971. [A. Schönhage and V. Strassen, Schnelle Multiplikation großer Zahlen ,… …   Wikipedia

  • Adaptive resonance theory — (ART) is a neural network architecture developed by Stephen Grossberg and Gail Carpenter. Learning model The basic ART system is an unsupervised learning model. It typically consists of a comparison field and a recognition field composed of… …   Wikipedia

  • Growing self-organizing map — A growing self organizing map (GSOM) is a growing variant of the popular self organizing map (SOM). The GSOM was developed to address the issue of identifying a suitable map size in the SOM. It starts with a minimal number of nodes (usually 4)… …   Wikipedia

  • Oja's rule — Oja s learning rule, or simply Oja s rule, named after a Finnish computer scientist Erkki Oja, is a model of how neurons in the brain or in artificial neural networks change connection strength, or learn, over time. It is a modification of the… …   Wikipedia

  • Monomial order — In mathematics, a monomial order is a total order on the set of all (monic) monomials in a given polynomial ring, satisfying the following two properties: If u < v and w is any other monomial, then uw<vw. In other words, the ordering… …   Wikipedia

  • Least mean squares filter — Least mean squares (LMS) algorithms are a class of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the… …   Wikipedia

  • Biological neuron model — A biological neuron model (also known as spiking neuron model) is a mathematical description of the properties of nerve cells, or neurons, that is designed to accurately describe and predict biological processes. This is in contrast to the… …   Wikipedia

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