Parallel Processing And Applied Mathematics:

To take full advantage of high performance computing, parallel applications must be carefully managed to guarantee quality of service and fairness in using shared resources. Scheduling for parallel computing is an interdisciplinary subject joining many fields, and the broadness of research yields an immense number and diversity of models for understanding scheduling problems.

This unique text/reference presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques drawn from more than ten years of research in this area.