Support

Support Options

Submit a Support Ticket

 

Resources: All

Finding a resource

Use the sorting or filtering options to sort results and/or narrow down the list of resources.

Use the 'Search' to find specific resources by title or description.

Search for Courses
  1. [Illinois]: Fish classification using back-propagation

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

    Trains a three-layered network of sigmoidal units using back-propagation to classify fish according to their lengths

  2. [Illinois]: Posterior probabilities of hypothetical fish classes

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

    Computes the posterior probabilities of each of three hypothetical fish classes using Bayes' rule

  3. [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)

  4. [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)

  5. [Illinois]: Posterior probability of a target given input for two senses (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 two modalities (i.e., visual and auditory)

  6. [Illinois]: Posterior probability of a target given input for two senses (delta)

    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 two modalities (i.e., visual and auditory)

  7. [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.

  8. Microbeam Dynamics with Varying Force Model

    01 Jul 2013 | Tools | Contributor(s): Saagar Unadkat

    Simulate the dynamics of microbeams with Knudsen Forces, Electrostatic and G-Forces.

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

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

    1. F. Patolsky et al., Electrical detection of single viruses, Proc. Natl. Acad. Sci. 101:14017-14022...

    2. Poster: Integrating ethics and policy into nanotechnology education

      08 Jul 2013 | Presentation Materials | Contributor(s): Mike Gorman

      Presented at the EEC meeting March 2012

    3. An Elementary Note on Skin Hydration Measurement Using Memristive Effect

      09 Jul 2013 | Publications | Contributor(s): Tukaram Dattatray Dongale

      The Memristor was predicted by Prof. L. Chua in 1971 and first prototype was reported by team of HP researcher. The memristor follows interesting relation in the view of magnetic flux and charge. There are tremendous applications areas emerged out in the framework of memristor in last few years....

    4. [Illinois] A Response of a Single Neuron with Positive Feedback

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

      This tool stimulates the pulse or step response of a single neuron with positive feedback

    5. The Road Ahead for Carbon Nanotube Transistors

      09 Jul 2013 | Online Presentations | Contributor(s): Aaron Franklin

      In this talk, recent advancements in the nanotube transistor field will be reviewed, showing why CNTFETs are worth considering now more than ever. Then, the material- and device-related challenges to realizing a nanotube-driven digital technology will be covered.

    6. [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

    7. What I've Learned Over Two Decades in MEMS

      10 Jul 2013 | Online Presentations | Contributor(s): 80547

      What do Sean Penn, Justin Bieber, Bob Marley, and MEMS have in common?

    8. [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.

    9. The Wright Flyer Crankcase: Precipitation Hardening in the First Aerospace Aluminum Alloys

      11 Jul 2013 | Online Presentations | Contributor(s): John Blendell

    10. [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.

    11. [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.

    12. High-Rate Processing and Advanced Emitter Structures for CIGS PV Module Manufacturing

      11 Jul 2013 | Online Presentations | Contributor(s): B. J. Stanbery

      Achieving both macroscopic homogeneity and nanoscale heterogeneity for non-stoichiometric multinary compounds is a critical challenge for the success of copper indium gallium selenide (CIGS) photovoltaic cells. Co-evaporation yields world record performance, but is also a high-temperature vacuum...

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.