Training fully connected networks with resistive memories: impact of device failures
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This paper presents a complementary metal–oxide– semiconductor (CMOS) implementation of a conscience mechanism used to improve the effectiveness of learning in the winnertakes- all (WTA) artificial neural networks (ANNs) realized at the transistor level. T ...
Institute of Electrical and Electronics Engineers2010
We address the problem of recognizing sequences of human interaction patterns in meetings, with the goal of structuring them in semantic terms. The investigated patterns, are inherently group-based (defined by the individual activities of meeting participa ...
We address the problem of recognizing sequences of human interaction patterns in meetings, with the goal of structuring them in semantic terms. The investigated patterns, are inherently group-based (defined by the individual activities of meeting participa ...
Memristors are passive circuit elements that behave as resistors with memory. The recently illustrated experimental realization of memristive behaviour of Polysilicon Nanowires has triggered interest in this concept, which is promising to a wide variety of ...
Research on artificial neural networks (ANNs) has been carried out for more than five decades. A renewed interest appeared in the 80's with the finding of powerful models like J. Hopfield's recurrent networks, T. Kohonen's self-organizing feature maps, and ...
Generalization networks are nonparametric estimators obtained from the application of Tychonov regularization or Bayes estimation to the hypersurface reconstruction problem. Under symmetry assumptions they are a particular type of radial basis function neu ...
Generalization networks are nonparametric estimators obtained from the application of Tychonov regularization or Bayes estimation to the hypersurface reconstruction problem. Under symmetry assumptions they are a particular type of radial basis function neu ...