RAAM/ComplexNet.m at master · gregwayne/RAAM · GitHub

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classdef ComplexNet

    properties

        net;
        sigma_sq_in;
        sigma_sq_out;
        t;

        X0;
        R2;

    end

    methods

        function obj = ComplexNet(N0,N1,N2,g,eta)

            obj.net             = SimpleNet(N0,N1,N2,g,eta);
            obj.t               = 1;
            obj.sigma_sq_in     = ones(N0,1);
            obj.sigma_sq_out    = ones(N2,1);

        end

        function obj = FProp(obj,X0)

            % Time is update at the beginning of every FProp
            obj.t   = obj.t + 1;
            t       = obj.t;

            % Divide by standard deviation of inputs
            obj.X0  = X0./sqrt(obj.sigma_sq_in);
            obj.net = obj.net.FProp(X0);
            % Multiply by standard deviation of outputs
            obj.R2  = obj.net.R2.*sqrt(obj.sigma_sq_out);

            obj.sigma_sq_in     = (1/t)*X0.^2 + obj.sigma_sq_in.*(t-1)/t;

        end

        function R2 = FastProp(obj,X0)

            X0  = X0./sqrt(obj.sigma_sq_in);
            R2  = obj.net.FastProp(X0).*sqrt(obj.sigma_sq_out);

        end

        function obj = ErrorLearn(obj,target)

            t           = obj.t;
            delta       = target - obj.R2;
            delta_net   = delta.*sqrt(obj.sigma_sq_out);
            obj.net     = obj.net.ErrorLearn(delta_net);

            obj.sigma_sq_out    = (1/t)*target.^2 + obj.sigma_sq_out.*(t-1)/t;

        end

        function obj = Tag(obj)

            obj.net = obj.net.Tag();

        end

        function obj = Untag(obj)

            obj.net = obj.net.Untag();

        end


    end

end