Sistema basado en redes neuronales digitales aplicado a la predicción climática en ambientes con microclima controlado

Abstract

This thesis describes the design, implementation and evaluation of FPGA Architecture of a Digital ANN (Artificial Neural Networks) by using four components: data memory, weights memory, neuron module, and control unit. All these components have a generic orthogonal structure in order to facilitate automatic generation from specific parameters. In a particular ANN design all of its components are generated with specific size, depending on two types of parameters: A) Topological (number of inputs and number of hidden neurons) will determine the size of the memories, the neuron processing time and the microprogram size. B) Architectonic (i.e. word size in bits and circuit granularity) will determine the precision of the results and the final ANN performance.