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Visual Explorations in Finance
Self-organizing maps (SOM) have proven to be of significant economic value in the areas of finance, economic and marketing applications. As a result, this area is rapidly becoming a non-academic technology. This book looks at near state-of-the-art SOM applications in the above areas, and is a multi-authored volume, edited by Guido Deboeck, a leading exponent in the use of computational methods in financial and economic forecasting, and by the originator of SOM, Teuvo Kohonen. The book contains chapters on applications of unsupervised neural networks using Kohonen's self-organizing map approach.
Coding as Literacy
Recent developments in computer science, particularly ”data-driven procedures“ have opened a new level of design and engineering. This has also affected architecture. The publication collects contributions on Coding as Literacy by computer scientists, mathematicians, philosophers, cultural theorists, and architects. The main focus in the book is the observation of computer-based methods that go beyond strictly case-based or problem-solution-oriented paradigms. This invites readers to understand Computational Procedures as being embedded in an overarching ”media literacy“ that can be revealed through, and acquired by, ”computational literacy“, and to consider the data processed in the above-mentioned methods as being beneficial in terms of quantum physics. ”Self-Organizing Maps“ (SOM), which were first introduced over 30 years ago, will serve as the concrete reference point for all further discussions.
Artificial Intelligence Applications and Innovations
Artificial Intelligence applications build on a rich and proven theoretical background to provide solutions to a wide range of real life problems. The ever expanding abundance of information and computing power enables researchers and users to tackle higly interesting issues for the first time, such as applications providing personalized access and interactivity to multimodal information based on preferences and semantic concepts or human-machine interface systems utilizing information on the affective state of the user. The purpose of the 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI) is to bring together researchers, engineers, and practitioners interested in the technical advances and business and industrial applications of intelligent systems. AIAI 2006 is focused on providing insights on how AI can be implemented in real world applications.
Hybrid Neural Systems
Hybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS'98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems. The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches.
Introduction to Text Analytics
Clear, nuanced introduction to digital text mining and data analysis specifically for students in digital humanities and computational social science.
Software Without Frontiers
Shows how to develop software which has the ability to interface cross-culturally utilizing the language of the user. Statements and messages can be captured in an abstract interlingual form and then the software can be ported from one language to another. Presents material on related issues including the commercial uses which drive decisions about globalization, the use of translation technology in localization, and the exploitation of software architectures in software internationalization. Annotation copyrighted by Book News, Inc., Portland, OR.
Image Analysis
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Neural Networks and Learning Machines
For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Matlab codes used for the computer experiments in the text are available for download at: http: //www.pearsonhighered.com/haykin/ Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.
Proceedings of the 2000 Congress on Evolutionary Computation
These volumes contain the proceedings of the 2000 Congress on Evolutionary Computation. The papers address: genetic programming; evolutionary optimization; the evolution of neural networks; evolutionary robotics; data mining with evolutionary algorithms; bio-inspired hardware; and more.
