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Ramachandran, Harshawardhan: Short term plasticity. A neuromorphic perspective. 2018
Inhalt
Declaration
Publications
Acknowledgements
Abstract
Contents
Acronyms
1 Introduction
1.1 Motivation of this study
1.2 Objectives of this research
1.3 Main contribution of this work
1.4 Structure of the thesis
2 Short-term synaptic plasticity
2.1 Introduction
2.2 Models of Short-Term Plasticity
2.3 Computational role of STP
2.3.1 Temporal filtering
2.3.2 Burst detection
2.3.3 Gain control
2.3.4 Direction selectivity
2.3.5 Encoding sound intensity
2.4 Conclusion
3 Sub-threshold neuromorphic hardware
3.1 Introduction
3.2 MOSFET
3.3 Sub-threshold characteristics of a transistor
3.3.1 Sub-threshold ohmic operation
3.3.2 Sub-threshold saturation operation
3.4 Basic building blocks of analog VLSI circuits
3.4.1 Diode-connected transistor
3.4.2 Current mirror
3.4.3 Source follower
3.4.4 Differential pair
3.5 Silicon synapse
3.6 Silicon neuron
3.7 Neuron array
3.8 Neuromorphic architecture
3.9 Conclusion
4 Neuromorphic design of short-term plasticity circuits
4.1 Introduction
4.2 Analog sub-threshold neuromorphic STD circuits
4.3 STP circuits with recovery control
4.3.1 STD circuit
4.3.2 STF circuit
4.4 STP circuits with feedback recovery control
4.4.1 STF circuit
4.4.2 STD circuit
4.5 Simulations of STP circuits
4.6 Fabrication and testing of STP circuits
4.7 Conclusion
5 Neuromorphic model for cricket calling song recognition network
5.1 Introduction
5.2 Neurobiology of cricket phonotaxis
5.3 Experimental methods
5.3.1 Stimulus
5.3.2 Network model
5.3.3 Computational primitives
5.4 Results
5.4.1 Behavioral data of cricket phonotaxis
5.5 Discussion
5.6 Conclusion
6 Conclusion
6.1 Advantages of neuromorphic approach
6.2 Future works
6.3 Outlook of neuromorphic engineering research
7 Appendix
7.1 Fabricated cricket calling song recognition network
7.2 STP based band-pass filter
7.3 Supplementary material