Artificial Adaptive Systems Using Auto Contractive Maps


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Artificial Adaptive Systems Using Auto Contractive Maps


Artificial Adaptive Systems Using Auto Contractive Maps

Author: Paolo Massimo Buscema

language: en

Publisher: Springer

Release Date: 2018-02-24


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This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book’s primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the “spin-net,” as a dynamic form of auto-associative memory.

Data Mining Applications Using Artificial Adaptive Systems


Data Mining Applications Using Artificial Adaptive Systems

Author: William J. Tastle

language: en

Publisher: Springer Science & Business Media

Release Date: 2012-08-27


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This volume directly addresses the complexities involved in data mining and the development of new algorithms, built on an underlying theory consisting of linear and non-linear dynamics, data selection, filtering, and analysis, while including analytical projection and prediction. The results derived from the analysis are then further manipulated such that a visual representation is derived with an accompanying analysis. The book brings very current methods of analysis to the forefront of the discipline, provides researchers and practitioners the mathematical underpinning of the algorithms, and the non-specialist with a visual representation such that a valid understanding of the meaning of the adaptive system can be attained with careful attention to the visual representation. The book presents, as a collection of documents, sophisticated and meaningful methods that can be immediately understood and applied to various other disciplines of research. The content is composed of chapters addressing: An application of adaptive systems methodology in the field of post-radiation treatment involving brain volume differences in children; A new adaptive system for computer-aided diagnosis of the characterization of lung nodules; A new method of multi-dimensional scaling with minimal loss of information; A description of the semantics of point spaces with an application on the analysis of terrorist attacks in Afghanistan; The description of a new family of meta-classifiers; A new method of optimal informational sorting; A general method for the unsupervised adaptive classification for learning; and the presentation of two new theories, one in target diffusion and the other in twisting theory.

Artificial Adaptive Systems in Medicine


Artificial Adaptive Systems in Medicine

Author: Massimo Buscema

language: en

Publisher: Bentham Science Publishers

Release Date: 2009-11-05


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"New Theories and Models for New Applications - This Ebook covers the emerging and most important theories underlying artificial intelligence applications in a variety of medical problems. It is written for physicians, researchers, engineers, statisticians"