Tools (101-120 of 149)

1. [Illinois]: AsynchUp

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

   This tool computes asynchronous updates of autoassociative networks.

2. [Illinois] KohonenSOM

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

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

3. [Illinois]: BUTDprobInference

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

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

4. [Illinois]: BUTDjointDistribution

   Tools | 16 Jul 2013 | 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

5. [Illinois]: Running Average

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

   This tool implements a running average of a noise series.

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

   Tools | 29 Jun 2013 | 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.

7. [Illinois]: Big Mess

   Tools | 26 Jun 2013 | 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.

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

   Tools | 28 Jun 2013 | 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)

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

   Tools | 28 Jun 2013 | 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)

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

    Tools | 28 Jun 2013 | 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)

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

    Tools | 28 Jun 2013 | 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)

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

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

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

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

    Tools | 28 Jun 2013 | 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

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

    Tools | 25 Jun 2013 | 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.

15. [Illinois]: Avoidance Learn Simulation

    Tools | 20 Jun 2013 | 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).

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

    Tools | 26 Jun 2013 | 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

17. Hydrodynamic Particle Trapping

    Tools | 14 Jun 2013 | Contributor(s):: Melikhan tanyerim@illinois.edu Tanyeri, John Feser, Nahil Sobh

    Simulates the motion of a nanoparticle in a hydrodynamic trap.

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

    Tools | 24 Jun 2013 | Contributor(s):: Lisa Sproat, NanoBio Node, Jessica S Johnson

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

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

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

    Simulates the responses of midbrain dopamine neurons using temporal difference learning

20. [Illinois]: Velocity storage and leakage

    Tools | 04 Jun 2013 | 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