Design of IIR Filters With Bayesian Model Selection and Parameter Estimation

Bayesian model selection and parameter estimation are used to address the problem of choosing the most concise filter order for a given application while simultaneously determining the associated filter coefficients. This approach is validated against simulated data and used to generate pole-zero representations of head-related transfer functions.