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Data clustering is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this book, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments.
This book summarizes effective and general approaches and frameworks in the investigation of bifurcation phenomena for functional differential equations (FDEs). It provides all the tools from bifurcation theory and contains examples and applications.
Abstract semilinear functional differential equations arise from many biological, chemical, and physical systems which are characterized by both spatial and temporal variables and exhibit various spatio-temporal patterns.
Contains results about the global dynamics defined by a class of delay differential equations which model basic feedback mechanisms and arise in a variety of applications such as neural networks. This book describes the geometric structure of a fundamental invariant set, which in special cases is the global attractor.
Containing stochastic non-linear models of biological systems, this book in biomathematics presents results for scalar and vector difference equations in random media with applications to the stochastic biological systems. It also offers an approach to the study of stochastic biological systems in random media such as random evolution approach.
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