Пример #1
0
        /// <summary>
        ///     Builds the structure of the neural network ready for training and testing
        /// </summary>
        public static void BuildStructure(Base inputLayer, Base outputLayer, List<Structure.Node.Base> inputLayerNodes, List<Structure.Node.Base> ouputLayerNodes, Network testNetworkStructure)
        {
            for (Int32 i = 0; i < 1; i++) inputLayerNodes.Add(new Structure.Node.Base(inputLayer, new Elliott()));

            inputLayer.SetNodes(inputLayerNodes);

            EchoReservoir echoLayer = new EchoReservoir(130, 0.4f, 0, 5, new Elliott());

            for (Int32 i = 0; i < 1; i++) ouputLayerNodes.Add(new Output(outputLayer, new Elliott()));
            outputLayer.SetNodes(ouputLayerNodes);

            inputLayer.ConnectFowardLayer(echoLayer);
            echoLayer.ConnectFowardLayer(outputLayer);

            testNetworkStructure.AddLayer(inputLayer);
            testNetworkStructure.AddLayer(echoLayer);
            testNetworkStructure.AddLayer(outputLayer);

            foreach (Base layer in testNetworkStructure.GetCurrentLayers()) layer.PopulateNodeConnections();
        }
Пример #2
0
        /// <summary>
        ///     Builds the structure of the neural network ready for training and testing
        /// </summary>
        public static void BuildStructure()
        {
            _InputLayer = new Base();
            _InputLayerNodes = new List<Structure.Node.Base>();
            for (Int32 i = 0; i < 1; i++) _InputLayerNodes.Add(new Structure.Node.Base(_InputLayer, new Elliott()));
            _InputLayer.SetNodes(_InputLayerNodes);

            EchoReservoir echoLayer = new EchoReservoir(130, 0.4f, 0, 5, new Elliott());

            _OutputLayer = new Base();
            _OuputLayerNodes = new List<Structure.Node.Base>();
            for (Int32 i = 0; i < 1; i++) _OuputLayerNodes.Add(new Output(_OutputLayer, new Elliott()));
            _OutputLayer.SetNodes(_OuputLayerNodes);

            _InputLayer.ConnectFowardLayer(echoLayer);
            echoLayer.ConnectFowardLayer(_OutputLayer);

            _TestNetworkStructure.AddLayer(_InputLayer);
            _TestNetworkStructure.AddLayer(echoLayer);
            _TestNetworkStructure.AddLayer(_OutputLayer);

            foreach (Base layer in _TestNetworkStructure.GetCurrentLayers()) layer.PopulateNodeConnections();
        }
        /// <summary>
        ///     Builds the structure of the neural network ready for training and testing
        /// </summary>
        public static void BuildStructure()
        {
            _InputLayer = new Base();
            _InputLayerNodes = new List<Structure.Node.Base>();
            for (Int32 i = 0; i < 1; i++) _InputLayerNodes.Add(new Structure.Node.Base(_InputLayer, new Tanh()));
            _InputLayer.SetNodes(_InputLayerNodes);

            EchoReservoir echoLayer = new EchoReservoir(50, 0.4f, 0, 30, new Tanh());

            _OutputLayer = new Base();
            _OuputLayerNodes = new List<Structure.Node.Base>();
            for (Int32 i = 0; i < 1; i++) _OuputLayerNodes.Add(new Output(_OutputLayer, new Tanh()));
            _OutputLayer.SetNodes(_OuputLayerNodes);

            _RecurrentLayer = new RecurrentContext(2, new Tanh());
            _RecurrentLayer.AddSourceNodes(_OuputLayerNodes);

            _InputLayer.ConnectFowardLayer(echoLayer);
            _RecurrentLayer.ConnectFowardLayer(echoLayer);

            echoLayer.ConnectFowardLayer(_OutputLayer);

            _TestNetworkStructure.AddLayer(_InputLayer);
            _TestNetworkStructure.AddLayer(_RecurrentLayer);
            _TestNetworkStructure.AddLayer(echoLayer);
            _TestNetworkStructure.AddLayer(_OutputLayer);

            foreach (Base layer in _TestNetworkStructure.GetCurrentLayers()) layer.PopulateNodeConnections();
            ((Structure.Node.RecurrentContext)_RecurrentLayer.GetNodes()[0]).OverrideRateOfUpdate(1);
        }