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Tags: nano/bio

Resources (21-40 of 423)

  1. [Illinois]: Perturbative Reinforcement Learning to Develop Distributed Representations

    10 Jul 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool trains three-layered networks of sigmoidal units to associate patterns.

    http://nanohub.org/resources/pertdistrep

  2. [Illinois]: Perturbative Reinforcement Learning Using Directed Drift

    10 Jul 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool trains two-layered networks of sigmoidal units to associate patterns using a real-valued adaptation of the directed drift algorithm.

    http://nanohub.org/resources/pertdd

  3. [Illinois]: Temporal Difference, Iterative Dynamic Programming, and Least Mean Squares

    11 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson

    This tool updates state values using the Temporal Difference Algorithm.

    http://nanohub.org/resources/tempdiff

  4. Crystalline Cellulose - Atomistic Toolkit

    17 Jul 2013 | Tools | Contributor(s): Mateo Gómez Zuluaga, Robert J. Moon, Fernando Luis Dri, Pablo Daniel Zavattieri

    Crystalline Cellulose - Atomistic Toolkit

    http://nanohub.org/resources/ccamt

  5. [Illinois] GEM4 Bionanotechnology Summer Institute 2013

    01 Aug 2013 | Workshops

    INSTITUTE FOCUS: Cancer Nanotechnology and Cellular Mechanics OBJECTIVES The overall objective is to enhance the ability to address overarching challenges in the areas of Cancer...

    http://nanohub.org/resources/19040

  6. [Illinois]: Direction Selectivity

    13 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool implements a simple direction selective network.

    http://nanohub.org/resources/dirselectivity

  7. [Illinois]: Predict Correct Set Up

    15 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool sets up a predictor-corrector model of target tracking

    http://nanohub.org/resources/predcorsetup

  8. [Illiniois]: SynchUp

    16 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool computes synchronous updates of autoassociative networks.

    http://nanohub.org/resources/synchup

  9. [Illinois]: AsynchUp

    16 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, NanoBio Node, Jessica S Johnson

    This tool computes asynchronous updates of autoassociative networks.

    http://nanohub.org/resources/asynchup

  10. [Illinois] KohonenSOM

    09 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, Jessica S Johnson, NanoBio Node

    This tool implements the Kohonen self-organizing map (SOM) algorithm

    http://nanohub.org/resources/kohonensom

  11. [Illinois]: BUTDprobInference

    17 Jul 2013 | Tools | Contributor(s): Bara Saadah, Jessica S Johnson, NanoBio Node

    This tool stimulates bottom-up/top-down processing in the visual system using probabilistic inference.

    http://nanohub.org/resources/butdprobinf

  12. [Illinois]: BUTDjointDistribution

    16 Jul 2013 | Tools | Contributor(s): Bara Saadah, Jessica S Johnson, NanoBio Node

    this tool simulates bottom-up/top-down processing in the visual system using the joint distribution

    http://nanohub.org/resources/butdjdist

  13. [Illinois]: Running Average

    10 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, Jessica S Johnson, NanoBio Node

    This tool implements a running average of a noise series.

    http://nanohub.org/resources/runningaverage

  14. [illinois] BioMEMS and Bionanotechnology: Integration of Life Sciences and Engineering at the Micro and Nanoscale

    10 Jul 2013 | Online Presentations | Contributor(s): Rashid Bashir

    Optical Society of America (OSA), University of Illinois Chapter, IEEE Electron Devices Society (EDS), University of Illinois Chapter, Micro and Nanotechnology Laboratory (MNTL),

    http://nanohub.org/resources/5985

  15. [Illinois]: Error Gradient Estimations Due to Perturbation of One Weight at a Time

    29 Jun 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool trains two-layered networks of sigmoidal units to associate patterns using perturbation of one weight at a time.

    http://nanohub.org/resources/pertgrad1by1

  16. MAE 6291 Lecture 07: FET, WGM and GMR as Signal Transducers

    07 Jul 2013 | Online Presentations | Contributor(s): jonathan silver

    F. Patolsky et al., Electrical detection of single viruses, Proc. Natl. Acad. Sci. 101:14017-14022 (2004) A. M. Armani et al., Label-free single molecule detection with optical...

    http://nanohub.org/resources/18851

  17. MAE 6291 Lecture 06: Single-Molecule Fluorescence, TIRF, FRET

    07 Jul 2013 | Online Presentations | Contributor(s): jonathan silver

    A. Jain et al., Probing cellular protein complexes using single-molecule pull-down. Nature 474: 484-489 (2012)

    http://nanohub.org/resources/18850

  18. [Illinois]: Big Mess

    26 Jun 2013 | Tools | Contributor(s): Bara Saadah

    This tool stimulates the pulse or step response of a neural network with ten input and ten output units that are randomly connected.

    http://nanohub.org/resources/bigmess

  19. [Illinois]: Posterior target probability given single-sensory input (delta rule)

    28 Jun 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of one modality (i.e., visual)

    http://nanohub.org/resources/unisensorydelta

  20. [Illinois]: Posterior probability of a target given single-sensory input (Bayes')

    28 Jun 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Computes the posterior probability of a target given sensory input of one modality (i.e., visual)

    http://nanohub.org/resources/unisensorybayes

nanoHUB.org, a resource for nanoscience and nanotechnology, is supported by the National Science Foundation and other funding agencies. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.