Systematic application of model reduction methods allows implementing this modeling principle and finding models of minimal complexity compatible with the data.
In the first step a sustained voiced speech signal characteristics are analyzed using autoregressive modeling principle and then the two sets of linear prediction (LPC) coefficients are obtained and converted to linear spectrum frequencies (LSF).
To validate the performance of the suggested method, multiple mathematical test functions are given to illustrate the modeling principles, procedures, and the efficiency and accuracy of HDMR models with problems of a wide scope of dimensionalities.
After a step by step introduction in modeling principles, procedures and results for different systems like activated sludge, wetlands, waste stabilization ponds and anaerobic systems are given.
Although the examples are given in lightweight aluminum and magnesium alloys for structural applications, the fundamental methodology and modeling principles are applicable to all materials and engineering applications.
In this chapter, by applying mass balance, continuity, and bioprocess modeling principles, steady-state models that describe quantitatively the behavior of these three organism groups are developed and the experimental data on which these models are based are described.
