Package model.MARK_II.connectTypes

Examples of model.MARK_II.connectTypes.SensorCellsToRegionRectangleConnect

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        Retina retina = new Retina(66, 66);
        Region region = new Region("Region", 8, 8, 4,
                percentMinimumOverlapScore, (int) desiredLocalActivity);

        AbstractSensorCellsToRegionConnect retinaToRegion = new SensorCellsToRegionRectangleConnect();
        retinaToRegion.connect(retina.getVisionCells(), region, 0, 0);

        SpatialPooler spatialPooler = new SpatialPooler(region);
        spatialPooler.setLearningState(true);
        TemporalPooler temporalPooler = new TemporalPooler(spatialPooler,
                (int) newSynapseCount);
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            String locationOfFileWithFileNameToSaveScore) throws IOException {
        Retina retina = new Retina(66, 66);
        Region region = new Region("Region", 8, 8, 1,
                percentMinimumOverlapScore, (int) desiredLocalActivity);

        AbstractSensorCellsToRegionConnect retinaToRegion = new SensorCellsToRegionRectangleConnect();
        retinaToRegion.connect(retina.getVisionCells(), region, 0, 0);

        SpatialPooler spatialPooler = new SpatialPooler(region);
        spatialPooler.setLearningState(true);

        retina.seeBMPImage("2.bmp");
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        // all images in MNIST dataset are 28 x 28 pixels
        Retina retina = new Retina(28, 28);
        Region region = new Region("Region", 8, 8, 1,
                percentMinimumOverlapScore, (int) desiredLocalActivity);

        AbstractSensorCellsToRegionConnect retinaToRegion = new SensorCellsToRegionRectangleConnect();
        retinaToRegion.connect(retina.getVisionCells(), region, 0, 0);

        SpatialPooler spatialPooler = new SpatialPooler(region);
        spatialPooler.setLearningState(true);

        int numberOfImagesToSee = 1000;
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        // images this oldRetina will see are all 66x66 pixels
        this.retina = new Retina(66, 66);

        this.region = new Region("Region", 8, 8, 3, 77.8, 1);

        AbstractSensorCellsToRegionConnect retinaToRegion = new SensorCellsToRegionRectangleConnect();
        retinaToRegion.connect(this.retina.getVisionCells(), this.region, 0, 0);

        this.spatialPooler = new SpatialPooler(this.region);
        this.spatialPooler.setLearningState(true);

        this.retina.seeBMPImage("2.bmp");
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    private void setUpColumnActivityAfterSeeingImage2() throws IOException {
        Retina retina = new Retina(66, 66);
        Region region = new Region("Region", 8, 8, 1, 50, 3);

        AbstractSensorCellsToRegionConnect retinaToRegion = new SensorCellsToRegionRectangleConnect();
        retinaToRegion.connect(retina.getVisionCells(), region, 0, 0);

        SpatialPooler spatialPooler = new SpatialPooler(region);
        spatialPooler.setLearningState(true);

        retina.seeBMPImage("2.bmp");
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        neocortex.addToCurrentRegion(new Rectangle(new Point(0, 0), new Point(125, 125)), L, 0, 0);

        // NOTE: I, J, K, & L are connected to different parts of the same Retina
        Retina retina = new Retina(1000, 1000);

        AbstractSensorCellsToRegionConnect opticNerve = new SensorCellsToRegionRectangleConnect();
        opticNerve.connect(retina.getVisionCells(new Rectangle(new Point(0, 0), new Point(500, 500))), I, 0, 0); // .getVisionCells(topLeftPoint, bottomRightPoint)
        opticNerve.connect(retina.getVisionCells(new Rectangle(new Point(0, 500), new Point(500, 1000))), J, 0, 0);
        opticNerve.connect(retina.getVisionCells(new Rectangle(new Point(500, 0), new Point(1000, 500))), K, 0, 0);
        opticNerve.connect(retina.getVisionCells(new Rectangle(new Point(500, 500), new Point(1000, 1000))), L, 0, 0);

        NervousSystem nervousSystem = new NervousSystem(neocortex, null, retina); // no LGN with circle surround input for now

        return nervousSystem;
    }
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        this.retina = new Retina(66, 66);

        this.region = new Region("Region name", 8, 8, 1, 77.8, 1);
        this.region.setInhibitionRadius(3);

        AbstractSensorCellsToRegionConnect retinaToRegion = new SensorCellsToRegionRectangleConnect();
        retinaToRegion.connect(this.retina.getVisionCells(), this.region, 0, 0);

        this.spatialPooler = new SpatialPooler(this.region);
        this.spatialPooler.setLearningState(true);
    }
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                unconnectedLGN, unconnectedRetina);

        // connect OldRetina to LGN
        Retina retina = nervousSystem.getPNS().getSNS().getRetina();
        LGN LGN = nervousSystem.getCNS().getBrain().getThalamus().getLGN();
        AbstractSensorCellsToRegionConnect opticNerve = new SensorCellsToRegionRectangleConnect();
        opticNerve.connect(retina.getVisionCells(), LGN.getRegion(), 0, 0);

        // connect LGN to very small part of V1 Region of Neocortex
        Neocortex neocortex = nervousSystem.getCNS().getBrain().getCerebrum()
                .getCerebralCortex().getNeocortex();
        AbstractRegionToRegionConnect regionToRegionConnect = new RegionToRegionRectangleConnect();
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    public void test_getActiveColumnPositionsAsString() throws IOException {
        Retina retina = new Retina(66, 66);

        Region region = new Region("region", 8, 8, 4, 50, 1);

        AbstractSensorCellsToRegionConnect connectType2 = new SensorCellsToRegionRectangleConnect();
        connectType2.connect(retina.getVisionCells(), region, 2, 2);

        SpatialPooler spatialPooler = new SpatialPooler(region);
        spatialPooler.setLearningState(true);

        // declare sets to test on
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    public void test_saveRegionObject() throws IOException {
        Region LGNRegion = new Region("LGN", 8, 8, 1, 50, 3);

        Retina retina = new Retina(66, 66);

        AbstractSensorCellsToRegionConnect retinaToLGN = new SensorCellsToRegionRectangleConnect();
        retinaToLGN.connect(retina.getVisionCells(), LGNRegion, 0, 0);

        // run spatial pooling on a image
        SpatialPooler spatialPooler = new SpatialPooler(LGNRegion);
        spatialPooler.setLearningState(true);
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Related Classes of model.MARK_II.connectTypes.SensorCellsToRegionRectangleConnect

  • model.MARK_I.vision.HowMARK_I_FitsInToBrainAnatomy
  • model.MARK_I.vision.NoiseInvarianceExperiment
  • model.MARK_II.parameters.FindOptimalParametersForSDR
  • model.MARK_II.parameters.FindOptimalParametersForSPandTP
  • model.MARK_II.parameters.SDRScoreCalculatorTest
  • model.MARK_II.SpatialPoolerTest
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  • model.util.JsonFileInputOutputTest
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