Abstract:
A method for synchronizing a wireless communication system is disclosed. A silence duration for a base station is determined based on the time required for a neighbor base station to obtain or maintain synchronization. All transmissions from the base station are ceased for the silence duration. Multiple base stations level may cease transmissions at the same time, thus mitigating interference.
Abstract:
Certain aspects of the present disclosure provide methods and apparatus for creating tags (static or dynamic) for input/output classes of a neural network model using supervised learning. The method includes augmenting a neural network model with a plurality of neurons and training the augmented network using spike timing dependent plasticity (STDP) to determine one or more tags.
Abstract:
A method for managing synapse plasticity in a neural network includes converting a first set of synapses from a plastic synapse type to a fixed synapse type. The method may also include converting a second set of synapses from the fixed synapse type to the plastic synapse type.
Abstract:
Methods and apparatus are provided for effecting modulation using global scalar values in a spiking neural network. One example method for operating an artificial nervous system generally includes determining one or more updated values for artificial neuromodulators to be used by a plurality of entities in a neuron model and providing the updated values to the plurality of entities.
Abstract:
A method for synchronizing a wireless communication system is disclosed. A silence duration for a base station is determined based on the time required for a neighbor base station to obtain or maintain synchronization. All transmissions from the base station are ceased for the silence duration. Multiple base stations level may cease transmissions at the same time, thus mitigating interference.