Homogeneity problem for basis expansion of functional data with applications to resistive memories Articles uri icon

authors

  • Aguilera, Ana M.
  • Acal, Christian
  • AGUILERA MORILLO, MARIA DEL CARMEN
  • Jimenez Molinos, Francisco
  • Roldan, Juan B.

publication date

  • August 2021

start page

  • 41

end page

  • 51

volume

  • 186

International Standard Serial Number (ISSN)

  • 0378-4754

Electronic International Standard Serial Number (EISSN)

  • 1872-7166

abstract

  • The homogeneity problem for testing if more than two different samples come from the same population is considered for the case of functional data. The methodological results are motivated by the study of homogeneity of electronic devices fabricated by different materials and active layer thicknesses. In the case of normality distribution of the stochastic processes associated with each sample, this problem is known as Functional ANOVA problem and is reduced to test the equality of the mean group functions (FANOVA). The problem is that the current/voltage curves associated with Resistive Random Access Memories (RRAM) are not generated by a Gaussian process so that a different approach is necessary for testing homogeneity. To solve this problem two different parametric and nonparametric approaches based on basis expansion of the sample curves are proposed. The first consists of testing multivariate homogeneity tests on a vector of basis coefficients of the sample curves. The second is based on dimension reduction by using functional principal component analysis of the sample curves (FPCA) and testing multivariate homogeneity on a vector of principal components scores. Different approximation numerical techniques are employed to adapt the experimental data for the statistical study. An extensive simulation study is developed for analyzing the performance of both approaches in the parametric and non-parametric cases. Finally, the proposed methodologies are applied on three samples of experimental reset curves measured in three different RRAM technologies.

subjects

  • Statistics

keywords

  • basis expansion of curves; functional data analysis; homogeneity tests; karhunen-lo√®ve expansion; p-splines; resistive switching process