Learning on Silicon

' This is an excellent book which takes the reader from the physical basis of learning on silicon to algorithms and architectures. The contributed chapters are authoritatively written and the material is well organized, strongly recommended to anyone interested in neuromorphic engineering, adaptive hardware systems.' A.G. Andreou, Johns Hopkins University

• Preface. Acknowledgements. 1. Learning on Silicon: A Survey; G. Cauwenberghs. Part I: Adaptive Sensory Processing. 2. Adaptive Circuits and Synapses using pFET Floating-Gate Devices; P. Hasler, et al. 3. Silicon Photoreceptors with Controllable Adaptive Filtering Properties; S.-C. Liu. 4. Analog VLSI System for Active Drag Reduction; V. Koosh, et al. Part II: Neuromorphic Learning. 5. Biologically-inspired Learning in Pulsed Neural Networks; T. Lehmann, R. Woodburn. 6. Spike Based Normalizing Hebbian Learning in an Analog VLSI Artificial Neuron; P. Hafliger, M. Mahowald. 7. Antidromic Spikes Drive Hebbian Learning in an Artificial Dendritic Tree; W.C. Westerman, et al. Part III: Learning Architecture. 8. ART1 and ARTMAP VLSI Circuit Implementation; T. Serrano-Gotarredona, B. Linares-Barranco. 9. Circuits for On-Chip Learning in Neuro-Fuzzy Controllers; F. Vidal-Verdu, et al. 10. Analog VLSI Implementation of Self-learning Neural Networks; T. Morie. 11. A 1.2 GFLOPS Neural Network Processor for Large-Scale Neural Network Accelerator Systems; Y. Kondo, et al. Part IV: Learning Dynamics. 12. Analog Hardware Implementation of Continuous-Time Adaptive Filter Structures; J.G. Harris, et al. 13. A Chip for Temporal Learning with Error Forward Propagation; F.M. Salam, H.-J. Oh. 14. Analog VLSI On-Chip Learning Neural Network with Learning Rate Adaptation; G.M. Bo, et al. Part V: Learning Systems. 15. Learning on CNN Universal Machine Chips; R. Carmona, et al. 16. Analog VLSI Parallel Stochastic Optimization for Adaptive Optics; R.T. Edwards, et al. 17. A Nonlinear Noise-Shaping Delta-Sigma Modulator with On-Chip Reinforcement Learning; G. Cauwenberghs. 18. A Micropower Adaptive Linear Transform Vector Quantiser; R.J. Coggins, et al. Index.