Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Apuntes de Redes Neuronales Artificiales   These handouts are designed for people who is just starting involved with the
topic artificial neural networks. We show how it works a single artificial
neuron (McCulloch & Pitt model), mathematically and graphically. We do explain
the delta rule, a learning algorithm to find the neuron weights. We also
present some examples in MATLAB/Octave. There are examples for classification
task for lineal and non-lineal problems. At the end, we present an artificial
neural network, a feed-forward neural network along its learning algorithm
backpropagation.
  -----
  Estos apuntes est\'an dise\~nados para personas que por primera vez se
introducen en el tema de las redes neuronales artificiales. Se muestra el
funcionamiento b\'asico de una neurona, matem\'aticamente y gr\'aficamente. Se
explica la Regla Delta, algoritmo deaprendizaje para encontrar los pesos de una
neurona. Tambi\'en se muestran ejemplos en MATLAB/Octave. Hay ejemplos para
problemas de clasificaci\'on, para problemas lineales y no-lineales. En la
parte final se muestra la arquitectura de red neuronal artificial conocida como
backpropagation.

11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin