This paper describes the use of dynamic Bayesian networks for the task of articulatory feature recognition. We show that by modeling the dependencies between a set of 6 multi-leve...
Abstract: Reservoir Computing (RC) systems are powerful models for online computations on input sequences. They consist of a memoryless readout neuron which is trained on top of a ...
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
We have fabricated a PCA (Principal Component Analysis) learning network in a FPGA (Field Programmable Gate Array) by using an asynchronous PDM (Pulse Density Modulation) digital ...
Synaptic runaway denotes the formationof erroneous synapses and premature functional decline accompanying activity-dependent learning in neural networks. This work studies synapti...