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Correlative Learning
Contributor(s): Chen, Zhe (Author)
ISBN: 0470044888     ISBN-13: 9780470044889
Publisher: Wiley-Interscience
OUR PRICE:   $191.85  
Product Type: Hardcover - Other Formats
Published: September 2007
Qty:
Annotation: This book bridges the communication gap between neuroscientists and engineers through the unifying theme of correlation-based learning

Developing brain-style signal processing or machine learning algorithms has attracted many sharp minds from a range of disciplines. Now, coauthored by four researchers with varying backgrounds in signal processing, neuroscience, psychology, and computer science, Correlative Learning unifies the many cross-fertilized ideas in computational neuroscience and signal processing in a common language that will help engineers understand and appreciate the human brain as a highly sophisticated biosystem for building more intelligent machines.

First, the authors present the necessary neuroscience background for engineers, and then go on to relate the common intrinsic structures of the learning mechanisms of the brain to signal processing, machine learning, kernel learning, complex-valued domains, and the ALOPEX learning paradigm.

This correlation-based approach to building complex, reliable (robust), and adaptive systems is vital for engineers, researchers, and graduate students from various fields of science and engineering. Figures, tables, worked examples, and case studies illustrate how to use computational tools for either helping to understand brain functions or fitting specific engineering applications, and a comprehensive bibliography covering over 1,000 references from major publications is included for further reading.

Additional Information
BISAC Categories:
- Computers | Intelligence (ai) & Semantics
- Computers | Neural Networks
- Medical | Neuroscience
Dewey: 612.82
LCCN: 2007006012
Series: Adaptive and Learning Systems for Signal Processing, Communications and Control
Physical Information: 1.14" H x 6.38" W x 9.31" (1.80 lbs) 480 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
Correlative Learning: A Basis for Brain and Adaptive Systems provides a bridge between three disciplines: computational neuroscience, neural networks, and signal processing. First, the authors lay down the preliminary neuroscience background for engineers. The book also presents an overview of the role of correlation in the human brain as well as in the adaptive signal processing world; unifies many well-established synaptic adaptations (learning) rules within the correlation-based learning framework, focusing on a particular correlative learning paradigm, ALOPEX; and presents case studies that illustrate how to use different computational tools and ALOPEX to help readers understand certain brain functions or fit specific engineering applications.