Esempio n. 1
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        /// <summary>
        /// Generate the network.
        /// </summary>
        /// <returns>The generated network.</returns>
        public BasicNetwork Generate()
        {
            ILayer layer = new BasicLayer(new ActivationBiPolar(), true,
                                          this.neuronCount);

            BasicNetwork result = new BasicNetwork(new BoltzmannLogic());

            result.SetProperty(BoltzmannLogic.PROPERTY_ANNEAL_CYCLES, this.annealCycles);
            result.SetProperty(BoltzmannLogic.PROPERTY_RUN_CYCLES, this.runCycles);
            result.SetProperty(BoltzmannLogic.PROPERTY_TEMPERATURE, this.temperature);
            result.AddLayer(layer);
            layer.AddNext(layer);
            layer.X = PatternConst.START_X;
            layer.Y = PatternConst.START_Y;
            result.Structure.FinalizeStructure();
            result.Reset();
            return(result);
        }
        public BasicNetwork Create()
        {
            BasicNetwork network = XOR.CreateTrainedXOR();

            XOR.VerifyXOR(network, 0.1);

            network.SetProperty("test", "test2");


            return(network);
        }
Esempio n. 3
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        /// <summary>
        /// Generate the neural network.
        /// </summary>
        /// <returns>The generated neural network.</returns>
        public BasicNetwork Generate()
        {
            BasicNetwork network = new BasicNetwork(new ART1Logic());

            int y = PatternConst.START_Y;

            ILayer   layerF1       = new BasicLayer(new ActivationLinear(), false, this.InputNeurons);
            ILayer   layerF2       = new BasicLayer(new ActivationLinear(), false, this.OutputNeurons);
            ISynapse synapseF1toF2 = new WeightedSynapse(layerF1, layerF2);
            ISynapse synapseF2toF1 = new WeightedSynapse(layerF2, layerF1);

            layerF1.Next.Add(synapseF1toF2);
            layerF2.Next.Add(synapseF2toF1);

            // apply tags
            network.TagLayer(BasicNetwork.TAG_INPUT, layerF1);
            network.TagLayer(BasicNetwork.TAG_OUTPUT, layerF2);
            network.TagLayer(ART1Pattern.TAG_F1, layerF1);
            network.TagLayer(ART1Pattern.TAG_F2, layerF2);

            layerF1.X = PatternConst.START_X;
            layerF1.Y = y;
            y        += PatternConst.INC_Y;

            layerF2.X = PatternConst.START_X;
            layerF2.Y = y;

            network.SetProperty(ARTLogic.PROPERTY_A1, this.A1);
            network.SetProperty(ARTLogic.PROPERTY_B1, this.B1);
            network.SetProperty(ARTLogic.PROPERTY_C1, this.C1);
            network.SetProperty(ARTLogic.PROPERTY_D1, this.D1);
            network.SetProperty(ARTLogic.PROPERTY_L, this.L);
            network.SetProperty(ARTLogic.PROPERTY_VIGILANCE, this.Vigilance);

            network.Structure.FinalizeStructure();

            return(network);
        }
        /// <summary>
        /// Generate the network.
        /// </summary>
        /// <returns>The generated network.</returns>
        public BasicNetwork Generate()
        {
            ILayer layer = new BasicLayer(new ActivationBiPolar(), true,
                    this.neuronCount);

            BasicNetwork result = new BasicNetwork(new BoltzmannLogic());
            result.SetProperty(BoltzmannLogic.PROPERTY_ANNEAL_CYCLES, this.annealCycles);
            result.SetProperty(BoltzmannLogic.PROPERTY_RUN_CYCLES, this.runCycles);
            result.SetProperty(BoltzmannLogic.PROPERTY_TEMPERATURE, this.temperature);
            result.AddLayer(layer);
            layer.AddNext(layer);
            layer.X = PatternConst.START_X;
            layer.Y = PatternConst.START_Y;
            result.Structure.FinalizeStructure();
            result.Reset();
            return result;
        }
Esempio n. 5
0
        /// <summary>
        /// Generate the neural network.
        /// </summary>
        /// <returns>The generated neural network.</returns>
        public BasicNetwork Generate()
        {
            BasicNetwork network = new BasicNetwork(new ART1Logic());

            int y = PatternConst.START_Y;

            ILayer layerF1 = new BasicLayer(new ActivationLinear(), false, this.InputNeurons);
            ILayer layerF2 = new BasicLayer(new ActivationLinear(), false, this.OutputNeurons);
            ISynapse synapseF1toF2 = new WeightedSynapse(layerF1, layerF2);
            ISynapse synapseF2toF1 = new WeightedSynapse(layerF2, layerF1);
            layerF1.Next.Add(synapseF1toF2);
            layerF2.Next.Add(synapseF2toF1);

            // apply tags
            network.TagLayer(BasicNetwork.TAG_INPUT, layerF1);
            network.TagLayer(BasicNetwork.TAG_OUTPUT, layerF2);
            network.TagLayer(ART1Pattern.TAG_F1, layerF1);
            network.TagLayer(ART1Pattern.TAG_F2, layerF2);

            layerF1.X = PatternConst.START_X;
            layerF1.Y = y;
            y += PatternConst.INC_Y;

            layerF2.X = PatternConst.START_X;
            layerF2.Y = y;

            network.SetProperty(ARTLogic.PROPERTY_A1, this.A1);
            network.SetProperty(ARTLogic.PROPERTY_B1, this.B1);
            network.SetProperty(ARTLogic.PROPERTY_C1, this.C1);
            network.SetProperty(ARTLogic.PROPERTY_D1, this.D1);
            network.SetProperty(ARTLogic.PROPERTY_L, this.L);
            network.SetProperty(ARTLogic.PROPERTY_VIGILANCE, this.Vigilance);

            network.Structure.FinalizeStructure();

            return network;
        }