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.