Performance of a signal-dependent autoregressive channel model

Recently, work has been published on a channel model that employs signal-de pendent autoregressive filters to accurately and efficiently model signal n onlinearities and media noise characteristics, such as signal-dependence an d correlation, which are common in magnetic recording signals, This paper e valuates the model's performance using 42 sets of spin-stand data that cove r a large range of head/media manufacturers and operating points.