Examples of ca.nengo.model.nef.impl.BiasOrigin

ca.nengo.model.nef.impl.BiasOrigin

Part of a projection in which each of the Nodes making up an Ensemble is a source of only excitatory or inhibitory connections.

The theory is presented in Parisien, Anderson & Eliasmith (2007).

Such a projection includes a "base" DecodedOrigin and DecodedTermination (a projection between these may have weights of mixed sign). The projection is expanded with a BiasOrigin a pair of BiasTerminations, and a new NEFEnsemble of interneurons. The make weight signs uniform, a projection is established between the BiasOrigin and BiasTermination, in parallel with the original projection. The effective synaptic weights that arise from the combination of these two projections are of uniform sign. However, the post-synaptic Ensemble receives extra bias current as a result. This bias current is cancelled by a projection from the BiasOrigin through the interneurons, to a second BiasTermination.

TODO: account for transformations in the Termination, which can change sign and magnitude of weights @author Bryan Tripp

//    Plotter.plot(probe.getData(), "mixed weights");
    float[] mixed = MU.transpose(DataUtils.filter(probe.getData(), .01f).getValues())[0];
    getError(reference, mixed);


    p.addBias(300, .005f, .01f, true, false);
    BiasOrigin bo = (BiasOrigin) pre.getOrigin("post_input");
    BiasTermination bt = (BiasTermination) post.getTermination("input (bias)");
    assertTrue(MU.min(getNetWeights(directWeights, bo, bt)) > -1e-10);
    network.run(-1.5f, 1);
//    Plotter.plot(probe.getData(), "positive non-optimal");
//    float[] positiveNonOptimal = MU.transpose(DataUtils.filter(probe.getData(), .01f).getValues())[0];

    network.addNode(input);
    network.addNode(source);
    network.addNode(dest);


    source.addDecodedTermination("input", MU.I(1), .005f, false); //OK
    BiasOrigin bo = source.addBiasOrigin(source.getOrigin(NEFEnsemble.X), 200, "interneurons", true); //should have -ve bias decoders
    network.addNode(bo.getInterneurons()); //should be backwards response functions
//**    bo.getInterneurons().addDecodedTermination("source", MU.I(1), .005f, false);
    
//    Plotter.plot(bo.getInterneurons());
//    Plotter.plot(bo.getInterneurons(), NEFEnsemble.X);

Examples of ca.nengo.model.nef.impl.BiasOrigin

Related Classes of ca.nengo.model.nef.impl.BiasOrigin