Etude du potentiel de creation de formes du quantron.
详细信息   
  • 作者:Hackenbeck-Lambert ; Julien.
  • 学历:Master
  • 年:2011
  • 毕业院校:Ecole Polytechnique
  • ISBN:9780494826058
  • CBH:MR82605
  • Country:France
  • 语种:English
  • FileSize:1648660
  • Pages:162
文摘
This document presents the study of pattern creation capacities of the quantron, a recent model of artificial neuron that describes the transmission of information at synapses with stochastic processes. Earlier works have been dedicated to the development of mathematical approximations that aim at the applicability of the model within the neural network domain. Rather, we propose an informatics implementation true to the original mathematical model that enables us to study its characteristics. Within the guidelines of pattern recognition, we explore the capacities of quantrons and of networks of quantrons to produce binary two dimensional images. Specifically, we had as an objective to determine the architectures and parameters of networks able to produce the 26 capital letters of the alphabet. First by varying the parameters of single quantrons within limits and rules determined by our prior understanding of the model, we obtain a great quantity of images which we are able to assemble in order to create a few first letters. By proceeding to the analysis of the inner workings of the quantrons producing the letters, we are able to improve their esthetics and at the same time obtain a better understanding of the model, which leads us to discover and demonstrate different new characteristics that give it strong image production capacities. Limitations are also brought to light for which we suggest ways to work around. In order to support the precision of the numeric approximations of the model, its effects are studied and carefully monitored. Finally, we propose equations that enable us to find parameter values that produce any desired image and make use of them in order to complete our collection of letters of the alphabet. The results suggest a promising future to the model and different avenues are suggested for later work to benefit from it.

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