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This comprehensive reference, for mathematical, engineering and social scientists, methodically discusses matrix positivity classes. The matrices studied have direct applications in data analysis, differential equations, mathematical programming, computational complexity, economic models, population biology, dynamical systems, control theory, etc.
This book gives a unified development of how the graph of a symmetric matrix influences the possible multiplicities of its eigenvalues. For mathematicians working with linear algebra, computation, and combinatorics, the book provides new information to extend the ideas to areas such as geometric multiplicities.
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