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This book provides a valuable resource on the design of neuromorphic intelligence, which serves as a computational foundation for building compact and low-power brain-inspired intelligent systems. The book introduces novel spiking neural network learning algorithms,...
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...
This book presents the design, analysis, and application of nonlinear adaptive filters with the goal of improving efficient performance (ie the convergence speed, steady-state error, and computational complexity). The authors present a nonlinear adaptive filter, which...
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