Correlative Learning (Simon Haykin).

Correlative Learning by Simon Haykin offers a comprehensive overview of the relationship between three important fields: computational neuroscience, neural network design, and signal processing techniques. Starting with a brief introduction to neuroscience fundamentals, the book goes on to discuss the role of correlations in both the human brain and the world of adaptive signal processing. The authors present a unified framework for understanding many established synaptic adaptation (learning) mechanisms within the context of correlative learning, focusing on the ALOPEX paradigm. Finally, the book offers case studies to illustrate how various computational tools and the ALOPEX approach can be used to better understand certain aspects of brain function or to solve specific engineering problems.