Artificial Immune Systems and Their Applications: With 15 Tables
Springer-Verlag GmbH, 1999 - Medical - 306 pages
Artificial immune systems are highly distributed systems based on the principles of the natural system. This is a new and rapidly growing field offering powerful and robust information processing capabilities for solving complex problems. Like artificial neural networks, artificial immune systems can learn new information, recall previously learned information, and perform pattern recognition in a highly decentralized fashion. This volume provides an overview of the immune system from the computational viewpoint. It discusses computational models of the immune system and their applications, and provides a wealth of insights on immunological memory and the effects of viruses in immune response. It will be of professional interest to scientists, academics, vaccine designers, and practitioners.
38 pages matching mechanism in this book
Results 1-3 of 38
What people are saying - Write a review
We haven't found any reviews in the usual places.
An Overview of Artificial Immune Systems
Some Applications of Artificial Immune Systems
50 other sections not shown
activated adaptive critics adaptive immune system affinity agent anti-virus antibody antigenic distance applications approach Artificial Immune Systems autonomous B-cell behavior Bersini Biol biological Boer building blocks clonal selection clones complex Computer Science cross-reactive detectors developed distributed dynamics effector Engineering epidemic strains equations example extended Kalman filter Figure free HIV function genetic algorithms hard locations idiotypic idiotypic network IEEE immune network immune response immunoid Immunol immunological memory implementation input Intelligent Control interactions Jisys system Kalman filter estimates Kalman filter method learning lymphocytes machine learning match mechanism memory cells module monitoring mutation natural immune system neural networks neurons node optimal original antigenic sin parameters pathogen patterns Perelson performance population prior infection problem production programs Q-learning receptors recognition repertoire RNA virus robot sample SGIN signal space model Sparse Distributed Memory specific stimulation level stochastic strings structure theory threshold tion vaccine Varela variables viruses Weisbuch