Seleção de Parâmetros de Regularização por Minimização de Distâncias Esperadas de Bregman
DOI:
https://doi.org/10.5540/03.2023.010.01.0094Palavras-chave:
Regularização, Problemas Inversos, Divergências de BregmanResumo
Técnicas de regularização são ferramentas importantes para a solução numérica de problemas mal-postos (no sentido de Hadamard). O presente trabalho apresenta um método para a seleção do parâmetro de regularização através da minimização de um estimador não tendencioso para o erro preditivo do regularizador. A técnica proposta generaliza métodos existentes através da possibilidade da utilização de preditores mais gerais baseados em divergências de Bregman. O método é aplicável a uma ampla gama de técnicas de regularização lineares ou não-lineares e a diversos modelos estocásticos para o ruído.
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