Natural Intelligence Neuromorphic Engineering

Natural Intelligence Neuromorphic Engineering provides readers with the most recent advances in deep learning, computational intelligence and Artificial Neural Networks (ANN), presenting detailed research and explanations of the physics and physiology principles used in developing natural intelligence for unsupervised learning of Blind Sources Separation (BSS). Author Harold Szu, a world-renowned pioneer in natural intelligence development, assembles a team of experts that cover the latest trends in deep learning, including sections on how to improve robust internal knowledge representation, big database data mining, and real time optical flow.

This collaborative work offers researchers and graduate students the most up-to-date information on the theories and key applications in natural intelligence and deep learning towards real-time, error-free and automatic target recognition.

• Covers natural intelligence uses in today's fast-advancing computational intelligence applications
• Features MATLAB codes in each chapter that will be made available as free downloads for readers
• Provides a short and concise explanation of the physics and physiological principles necessary for developing natural intelligence through unsupervised learning and blind sources separation (BSS)