Class Neuron is abstract, and therefore you must instantiate one ... these classes provide a powerful and fully functional implementation for the groundwork of an ANN (Artificial Neural Netork). The ...

Additionally, similar to other state-based neural networks like LSTMs, and in contrast to feedforward ANN architectures, networks of adapting spiking neurons require per-neuron local memory to store ...

@inproceedings{ijcai2022p347, title = {Signed Neuron with Memory: Towards Simple, Accurate and High-Efficient ANN-SNN Conversion}, author = {Wang, Yuchen and Zhang, Malu and Chen, Yi and Qu, Hong}, ...

This is accomplished by taking a multi-layer network and using a training data set to configure the weights associated with each ‘neuron ... matrix of the ANN’s input-output gradients ...

A neuron's state is computed from the input signals from connected ... activation function because it replaces the usual activations in the output layer of the ANN, but it is more like a distinct ...