There is a need for a method that can detect the number of components within multi b-value diffusion-weighted imaging. In particular, this would aid in the identification and correction of partial volume effects (PVE) within the brain. A PVE model was simulated to contain varying ratios of cerebrospinal fluid and white matter. Multi-exponential fitting methods were applied and found to be unsuccessful in identifying the number of components within the model. A novel fitting method, the Autoregressive Discrete Acquisition Points Transformation, was applied to simulations. Following manipulation through the discrete Z-domain, the number of components were correctly identified.