Tags: nano/bio

Tools (41-60 of 80)

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

    02 Jul 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

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

    01 Jul 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

  3. [Illinois]: Posterior probability of a target given input for two senses (Bayes')

    01 Jul 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)

    http://nanohub.org/resources/bisensorybayes

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

    01 Jul 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)

    http://nanohub.org/resources/bisensorydelta

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

    01 Jul 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

    http://nanohub.org/resources/fishbayesrule

  6. [Illinois]: Fish classification using back-propagation

    01 Jul 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

    http://nanohub.org/resources/fishbackprop

  7. [Illinois]: Avoidance Learn Simulation with 'Call' Neuron

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

    This script simulates avoidance learning as a reinforcement learning with two upper motoneurons (sumo and fumo) and one "call" neuron.

    http://nanohub.org/resources/avoidlearncall

  8. [Illinois]: Avoidance Learn Simulation

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

    This script simulates avoidance conditioning as reinforcement learning with two upper motoneurons (SUMO and FUMO).

    http://nanohub.org/resources/avoidlearn

  9. [Illinois]: Sigmoidal unit training with the delta rule

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

    Uses the delta rule to train a single sigmoidal unit with feedback to simulate the responses of neurons in the parabigeminal nucleus

    http://nanohub.org/resources/pbndeltarule

  10. Hydrodynamic Particle Trapping

    26 Jun 2013 | Tools | Contributor(s): Melikhan tanyerim@illinois.edu Tanyeri, John Feser, Nahil Sobh

    Simulates the motion of a nanoparticle in a hydrodynamic trap.

    http://nanohub.org/resources/particletrap

  11. [Illinois]: Predictor-corrector simulation of parabigeminal nucleus neural responses

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

    Implements a predictor-corrector simulation of the responses of neurons in the parabigeminal nucleus

    http://nanohub.org/resources/pbnpredict

  12. [Illinois]: Midbrain dopamine neuron responses to temporal-difference learning

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

    Simulates the responses of midbrain dopamine neurons using temporal difference learning

    http://nanohub.org/resources/midbraindopamin

  13. [Illinois]: Velocity storage and leakage

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

    Implements the parallel-pathway and positive-feedback models of velocity storage, and the negative-feedback model of velocity leakage

    http://nanohub.org/resources/velstoreleak

  14. [Illinois]: Kohonen self-organizing map (SOM) algorithm

    21 Jun 2013 | Tools | Contributor(s): Bara Saadah, John Feser, NanoBio Node, Jessica S Johnson

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

    http://nanohub.org/resources/tonotopicsom

  15. Locust-flight central pattern generator

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

    Implements a linear version of Wilson's model of the locust-flight central pattern generator

    http://nanohub.org/resources/wilsoncpg

  16. Two-unit oculomotor integrator

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

    Implements the two-unit model of the integrator of the oculomotor system

    http://nanohub.org/resources/twounitintegrat

  17. [Illinois]: Two leaky integrators in series

    20 Jun 2013 | Tools | Contributor(s): Lisa L Sproat, John Feser, Jessica S Johnson, NanoBio Node

    Implements a model having two units (leaky integrators) in series, each with recurrent, excitatory self-connections allowing the units to exert positive feedback on themselves

    http://nanohub.org/resources/twoleakseries

  18. Accurate Chemical Master Equation (ACME)

    20 Jun 2013 | Tools | Contributor(s): Youfang Cao, Anna Terebus, John Feser, Nahil Sobh, Jie Liang

    Direct solution method of discrete Chemical Master Equation (dCME) for the steady state, the time evolution of full probability landscapes, and the first passage time distribution (FPTD) in...

    http://nanohub.org/resources/fbsdcme

  19. [Illinois]: Gill withdrawal habituation

    20 Jun 2013 | Tools | Contributor(s): John Feser, Jessica S Johnson, NanoBio Node

    A very simple simulation of habituation of the Aplysia gill withdrawal reflex.

    http://nanohub.org/resources/habituationgwr

  20. Pattern Formation in Bacterial Populations

    22 May 2013 | Tools | Contributor(s): Ting Lu, John Feser, Nahil Sobh, Pratik Naik

    Synthetic biology tool for engineering patterning systems.

    http://nanohub.org/resources/patform