: We present the implementation of on-line Hebbian learning for NESPINN, the Neurocomputer for the simulation of spiking neurons. In order to support various forms of Hebbian learn...
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
One of the most difficult problems in using dynamic reservoirs like echo state networks for signal processing is the choice of reservoir network parameters like connectivity or spe...
In this paper, a neural network controller for constrained robot manipulators is presented. A feedforward neural network is used to adaptively compensate for the uncertainties in ...
Abstract—This paper presents a novel study on how to distribute neural networks in a wireless sensor networks (WSNs) such that the energy consumption is minimized while improving...