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Neural Computation, ISSN 0899-7667, 06/2018, Volume 30, Issue 6, pp. 1542 - 1572
Journal Article
Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, 9/2013, Volume 110, Issue 39, pp. 15512 - 15513
Journal Article
IEEE Reviews in Biomedical Engineering, ISSN 1937-3333, 2010, Volume 3, Issue 1, pp. 106 - 119
Journal Article
NEURAL COMPUTATION, ISSN 0899-7667, 06/2018, Volume 30, Issue 6, pp. 1542 - 1572
Many recent generative models make use of neural networks to transform the probability distribution of a simple low-dimensional noise process into the complex... 
NEUROSCIENCES | BAYESIAN-INFERENCE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Learning | Lower bounds | Multilayers | Statistical analysis | Noise | Neural networks | Back propagation | Probabilistic models | Biological activity | Synapses | Distribution | Probability
Journal Article
1999, Analog circuits and signal processing, ISBN 9780792385554, Volume SECS 512, vii, 425
Book
Journal Article
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, ISSN 1557-170X, 07/2018, Volume 2018, pp. 2627 - 2630
In neural electrophysiology, spike sorting allows to separate different neurons from extracellularly measured recordings. It is an essential processing step in... 
Journal Article
Journal Article
IEEE Transactions on Circuits and Systems II: Express Briefs, ISSN 1549-7747, 12/2016, Volume 63, Issue 12, pp. 1161 - 1165
This brief presents a CMOS charge buffer with femtofarad-range input capacitance for applications in capacitive electropotential sensing. We analyze and verify... 
CMOS | Voltage measurement | near-field communication | noncontact electropotential sensor | Gain measurement | Capacitance | Frequency measurement | Sensors | Impedance | Capacitive sensing | Gain | parasitic capacitance | Integrated circuits | Research | Impedance (Electricity) | Semiconductor chips
Journal Article
Frontiers in Neuroscience, ISSN 1662-4548, 08/2018, Volume 12, p. 608
Error backpropagation is a highly effective mechanism for learning high-quality hierarchical features in deep networks. Updating the features or weights in one... 
Backpropagation | Biological learning | Supervised learning | Hardware accelerators | Local errors | biological learning | local errors | hardware accelerators | NEUROSCIENCES | supervised learning | backpropagation | Cognitive learning | Research | Neural networks | Error analysis (Mathematics)
Journal Article
IEEE Journal of Solid-State Circuits, ISSN 0018-9200, 11/2016, Volume 51, Issue 11, pp. 2664 - 2678
Journal Article
IEEE Transactions on Circuits and Systems I: Regular Papers, ISSN 1549-8328, 7/2019, pp. 1 - 13
Journal Article
FRONTIERS IN NEUROSCIENCE, ISSN 1662-453X, 01/2014, Volume 7, p. 272
Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as... 
Markov chain monte carlo | recurrent neural network | NEURONS | neuromorphic cognition | NETWORKS | synaptic plasticity | generative model | MODEL | COGNITION | NEUROSCIENCES | Generative Model | Markov chain Monte Carlo | Neuromorphic Cognition
Journal Article
IEEE Transactions on Biomedical Circuits and Systems, ISSN 1932-4545, 12/2015, Volume 9, Issue 6, pp. 753 - 754
Presents the introductory editorial from this issue of the publication. 
Journal Article
IEEE Transactions on Biomedical Circuits and Systems, ISSN 1932-4545, 12/2015, Volume 9, Issue 6, pp. 753 - 754
Journal Article
IEEE Transactions on Biomedical Circuits and Systems, ISSN 1932-4545, 12/2015, Volume 9, Issue 6, pp. 753 - 754
Journal Article
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