Data storage device adjusting refresh monitor based on a learning based feedback control

A data storage device, comprising:

• a magnetic media;
• a head actuated over the magnetic media;
• and
• control circuitry configured to:
• maintain a reinforcement learning based refresh monitor for a refresh zone of the magnetic media;
• analyze a read operation to determine a level of damage to the data occurring at the location being read;
• update one or more probability distributions based on that determined level of damage;
• determine an updated weight associated with a damage per write count for a location within the refresh zone;
• use the updated weight to control a frequency of refresh operations to refresh data in the refresh zone;
• update a distribution curve;
• calculate a new estimated degree of data degradation per write;
• and
• increment a refresh counter based on the calculated new estimated degree of data degradation per write.

A method of mitigating adjacent track interference, the method comprising:

• maintaining a reinforcement learning based refresh monitor for a refresh zone of the magnetic media, the reinforcement learning being based on one or more probability distributions correlated to respective write counts being tracked by the refresh monitor;
• analyzing a read operation;
• deriving a damage metric from a read operation to determine a level of damage occurring at the location being read;
• updating one or more probability distributions based on the damage metric;
• using the updated one or more probability distributions to control frequency of refresh operations in the refresh zone;
• updating a distribution curve;
• calculating a new estimated degree of data degradation per write;
• and
• incrementing a refresh counter based on the calculated new estimated degree of data degradation per write.