David Howard Goldberg
Affiliations: | 2004 | Johns Hopkins University, Baltimore, MD |
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Parents
Sign in to add mentor| Andreas Andreou | grad student | 2004 | Johns Hopkins | |
| (Efficient spike communication and computation in biological and engineered systems.) | ||||
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Publications
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| Gardner D, Banfelder J, Chan E, et al. (2011) Towards Massively-Parallel Analytic Capabilities for Multielectrode Recordings Biophysical Journal. 100: 95a |
| Repucci MA, Goldberg DH, Chan E, et al. (2010) Neuroanalysis.Org: Information-Theoretic and Extended Analyses of Neural Coding Biophysical Journal. 98: 141a |
| Goldberg DH, Victor JD, Gardner EP, et al. (2009) Spike train analysis toolkit: enabling wider application of information-theoretic techniques to neurophysiology. Neuroinformatics. 7: 165-78 |
| Goldberg DH, Andreou AG. (2007) Distortion of neural signals by spike coding. Neural Computation. 19: 2797-839 |
| Victor JD, Goldberg DH, Gardner D. (2007) Dynamic programming algorithms for comparing multineuronal spike trains via cost-based metrics and alignments. Journal of Neuroscience Methods. 161: 351-60 |
| Goldberg DH, Andreou AG, Julián P, et al. (2006) VLSI implementation of an energy-aware wake-up detector for an acoustic surveillance sensor network Acm Transactions On Sensor Networks. 2: 594-611 |
| Julián P, Andreou AG, Goldberg DH. (2006) A low-power correlation-derivative CMOS VLSI circuit for bearing estimation Ieee Transactions On Very Large Scale Integration (Vlsi) Systems. 14: 207-212 |
| Julián P, Andreou AG, Riddle L, et al. (2004) A comparative study of sound localization algorithms for energy aware sensor network nodes Ieee Transactions On Circuits and Systems I: Regular Papers. 51: 640-648 |
| Goldberg DH, Andreou AG. (2004) Spike communication of dynamic stimuli: Rate decoding versus temporal decoding Neurocomputing. 58: 101-107 |
| Goldberg DH, Cauwenberghs G, Andreou AG. (2001) Probabilistic synaptic weighting in a reconfigurable network of VLSI integrate-and-fire neurons. Neural Networks : the Official Journal of the International Neural Network Society. 14: 781-93 |