FAIRsharing record for: PyNN
收藏Mendeley Data2024-02-04 更新2024-06-30 收录
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This FAIRsharing record describes: The PyNN API aims to support modelling at a high-level of abstraction (populations of neurons, layers, columns and the connections between them) while still allowing access to the details of individual neurons and synapses when required. PyNN provides a library of standard neuron, synapse and synaptic plasticity models, which have been verified to work the same on the different supported simulators. PyNN also provides a set of commonly-used connectivity algorithms (e.g. all-to-all, random, distance-dependent, small-world) but makes it easy to provide your own connectivity in a simulator-independent way, either using the Connection Set Algebra or by writing your own Python code. PyNN has been developed as a procedural description in Python which can be used to instantiate a network across multiple simulators.
创建时间:
2024-02-04



