6533b835fe1ef96bd12a0038
RESEARCH PRODUCT
Non-linear neuro-inspired circuits and systems: Processing and learning issues
Luca PatanéRoland StraussPaolo Arenasubject
Network architectureQuantitative Biology::Neurons and Cognitionbusiness.industryComputer scienceReservoir computingEnergy Engineering and Power TechnologyNonlinear systemBasic learningEngineering (all)Key (cryptography)Selection (linguistics)Mathematics (all)Biotechnology; Chemical Engineering (all); Mathematics (all); Materials Science (all); Energy Engineering and Power Technology; Engineering (all)Chemical Engineering (all)Artificial intelligenceMaterials Science (all)businessRealization (systems)Electronic circuitBiotechnologydescription
In this chapter the main elements useful for the design and realization of the neural architectures reported in the following chapters will be presented. Considering spiking and non-spiking neurons, the models used for implementing each of them, the synaptic models, the basic learning and plasticity algorithms and the network architectures will be introduced and analysed. The key elements that led to their selection and application in the developed neuro-inspired systems will be discussed briefly.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-01-01 |