From 41c6409ebe6520b6d50374117dfae626d68daed9 Mon Sep 17 00:00:00 2001 From: coolneng Date: Thu, 1 Jul 2021 04:18:48 +0200 Subject: [PATCH] Conclude AI chapter --- Dissertation.org | 17 ++++++++++- Dissertation.pdf | Bin 814343 -> 820039 bytes assets/bibliography.bib | 65 +++++++++++++++++++++++++++++++++++++++- 3 files changed, 80 insertions(+), 2 deletions(-) diff --git a/Dissertation.org b/Dissertation.org index 225fcdd..76861ed 100644 --- a/Dissertation.org +++ b/Dissertation.org @@ -8,6 +8,7 @@ #+PANDOC_OPTIONS: csl:assets/ieee.csl #+PANDOC_OPTIONS: pdf-engine:xelatex #+PANDOC_OPTIONS: top-level-division:chapter +#+PANDOC_OPTIONS: mathjax:t #+PANDOC_METADATA: link-citations:t * Resumen @@ -114,13 +115,27 @@ Una neurona artificial es un modelo de una neurona biológica, cada neurona reci #+NAME: fig:artificial-neuron [[./assets/figures/artificial-neuron.png]] -Una red neuronal artificial (ANN) es una red de capas de neuronas artificiales. Una ANN está formada por una capa de entrada, capas ocultas y una capa de salida. Las neuronas de una capa están conectadas, total o parcialmente, a las neuronas de la capa siguiente. También son posibles las conexiones de retroalimentación con las capas anteriores. La estructura típica de una ANN es la siguiente: +El proceso de activación se puede expresar como un modelo matemático: + +\begin{equation} +y= f \left(\sum\limits_{i=0}^{n} w_{i}x_{i} - T \right) +\end{equation} + +donde $y$ es la salida del nodo, $f$ es la función de activación, $w_i$ es el peso de la entrada $x_{i}$ , y $T$ es el valor del umbral. cite:Zou2009 + +Una red neuronal artificial (ANN) es una red de capas de neuronas artificiales. Una ANN está formada por una capa de entrada, capas ocultas y una capa de salida. Las neuronas de una capa están conectadas, total o parcialmente, a las neuronas de la capa siguiente. También son posibles las conexiones de retroalimentación con las capas anteriores. cite:book:80129 La estructura típica de una ANN es la siguiente: + +\clearpage #+CAPTION: Estructura de una red neuronal artificial cite:book:80129 #+ATTR_HTML: :height 30% :width 50% #+NAME: fig:neural-network [[./assets/figures/neural-network.png]] +Los principios básicos de las redes neuronales artificiales fueron formulados por primera vez en 1943, y el perceptrón, que históricamente es posiblemente la primera neurona artificial, se propuso en 1958. cite:book:2610592 Sin embargo, estos modelos no fueron populares hasta mediados de la década de 1980, cuando se reinventó el algoritmo de /back-propagation/. cite:book:771224 + +En la actualidad, los avances tanto en potencia de cálculo del /hardware/, especialmente en las tarjetas gráficas (GPU) cite:Cireşan2010, como la disponibilidad de grandes /datasets/ cite:book:771224 han dado lugar al /Deep Learning/. + ** Hacia el Deep Learning * Estado del arte 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