The first truly up-to-date look at the theory and capabilities of nonlinear dynamical systems that take the form of feedforward neural network structures Considered one of the most important types of structures in the study of neural networks and neural-like networks, feedforward networks incorporating dynamical elements have important properties and are of use in many applications. Specializing in experiential knowledge, a neural network stores and expands its knowledge base via strikingly human routes-through a learning process and information storage involving interconnection strengths known as synaptic weights. In Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives, six leading authorities describe recent contributions to the development of an analytical basis for the understanding and use of nonlinear dynamical systems of the feedforward type, especially in the areas of control, signal processing, and time series analysis. Moving from an introductory discussion of the different aspects of feedforward neural networks, the book then addresses: * Classification problems and the related problem of approximating dynamic nonlinear input-output maps * The development of robust controllers and filters * The capability of neural networks to approximate functions and dynamic systems with respect to risk-sensitive error * Segmenting a time series It then sheds light on the application of feedforward neural networks to speech processing, summarizing speech-related techniques, and reviewing feedforward neural networks from the viewpoint of fundamental design issues. An up-to-date and authoritative look at the ever-widening technical boundaries and influence of neural networks in dynamical systems, this volume is an indispensable resource for researchers in neural networks and a reference staple for libraries.

Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives

Computers & Technology

Haykin, Simon

Principe, José C.

Sandberg, Irwin W.

Lo, James T.

Fancourt, Craig L.

Katagiri, Shigeru

Certification

Wiley-Interscience

Like no other text in this field, authors Jose C. Principe, Neil R. Euliano, and W. Curt Lefebvre have written a unique and innovative text unifying the concepts of neural networks and adaptive filters into a common framework. 
The text is suitable for senior/graduate courses in neural networks and adaptive filters. It offers over 200 fully functional simulations (with instructions) to demonstrate and reinforce key concepts and help the reader develop an intuition about the behavior of adaptive systems with real data. This creates a powerful self-learning environment highly suitable for the professional audience.

Neural and Adaptive Systems: Fundamentals through Simulations

Euliano, Neil R.

Lefebvre, W. Curt

Computer Science

wiley

We have come to know that our ability to survive and grow as a nation to a very large degree depends upon our scientific progress. Moreover, it is not enough simply to keep 1 abreast of the rest of the world in scientific matters. We must maintain our leadership. President Harry Truman spoke those words in 1950, in the aftermath of World War II and in the midst of the Cold War. Indeed, the scientific and engineering leadership of the United States and its allies in the twentieth century played key roles in the successful outcomes of both World War II and the Cold War, sparing the world the twin horrors of fascism and totalitarian communism, and fueling the economic prosperity that followed. Today, as the United States and its allies once again find themselves at war, President Truman’s words ring as true as they did a half-century ago. The goal set out in the Truman Administration of maintaining leadership in science has remained the policy of the U. S. Government to this day: Dr. John Marburger, the Director of the Office of Science and Technology (OSTP) in the Executive Office of the President, made remarks to that effect during his 2 confirmation hearings in October 2001. The United States needs metrics for measuring its success in meeting this goal of maintaining leadership in science and technology. That is one of the reasons that the National Science Foundation (NSF) and many other agencies of the U. S.

Brain-Computer Interfaces: An international assessment of research and development trends

Business & Money

Berger, Theodore W.

Chapin, John K.

Gerhardt, Greg A.

McFarland, Dennis J.

Soussou, Walid V.

Taylor, Dawn M.

Tresco, Patrick A.

Economics

Springer

Information Theoretic Learning: Renyi's Entropy and Kernel Perspectives (Information Science and Statistics)

This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.

This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.

This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectives and results in a single resource for students and practitioners in relevant application fields. Each chapter starts with a brief review of fundamentals, presents the material focused on the most important properties and evaluates comparatively the models discussing free parameters and their effect on the results. Proofs are provided at the end of each chapter. The book is geared to senior undergraduates with a basic understanding of linear algebra, signal processing and statistics, as well as graduate students or practitioners with experience in Kalman filtering.

Kalman Filtering Under Information Theoretic Criteria

Chen, Badong

Zheng, Nanning

Dang, Lujuan

This study gathered information on global status and trends in brain-computer interface (BCI) research to disseminate to government decision makers and the research community. It provides a worldwide snapshot of current research and development trends in BCI.

Berger, Theodore W. W.

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Books by Principe, José C.