The embedded soft computing approach in wireless sensor networks is suggested. This approach means a combination of embedded fuzzy logic and neural networks models for information...
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 ...