A taxonomic classification of dedicated microprocessor applications |
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| Affiliation: | 1. Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634, USA;2. AI Research Institute for Science and Engineering (AIRISE), Clemson University, Clemson, SC 29634, USA;1. Center for Healthcare Advancement & Outcomes, Baptist Health South Florida, Miami, FL, USA;2. Department of Internal Medicine, Brandon Regional Hospital, Brandon, FL, USA;3. Department of Internal Medicine, Ocala Regional Medical Center, Ocala, FL, USA;4. Department of Internal Medicine, West Marion Community Hospital, Ocala, FL, USA;5. Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA;6. Department of Internal Medicine, Loyola University Medical Center, Maywood, IL, USA;7. Ciccarone Preventive Cardiology Center, Johns Hopkins Hospital, Baltimore, MD, USA;8. Department of Epidemiology, Robert Stempel College of Public Health, Florida International University, Miami, FL, USA;9. Department of Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA |
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| Abstract: | The principles and uses of taxonomic classification for dedicated microprocessor applications are discussed and a classification is proposed. A population of devices, produced by the author, is mapped into the classification schema and typical characteristics of devices used in particular applications are estimated. It is suggested that the taxonomically derived characters may be of value for expert system design programs and in producing more efficient designs for dedicated microprocessor applications. |
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