implement fullyconnectedlayer() from scratch in matlab

main.m
classdef FullyConnectedLayer
    properties
        inputSize
        outputSize
        weights
        bias
        dLdW
        dLdB
    end
    
    methods
        function obj = FullyConnectedLayer(inputSize, outputSize)
            obj.inputSize = inputSize;
            obj.outputSize = outputSize;
            
            % Initialize weights with Xavier initialization
            variance = 2/(inputSize+outputSize);
            obj.weights = sqrt(variance)*randn(outputSize, inputSize);
            
            % Initialize bias to zero
            obj.bias = zeros(outputSize, 1);
        end
        
        function output = forward(obj, input)
            % Compute output as matrix product of weights and input
            output = obj.weights*input + obj.bias;
        end
        
        function [dLdInput, obj] = backward(obj, input, gradOutput, learningRate)
            % Compute gradients of loss with respect to weights and bias
            obj.dLdW = gradOutput*input';
            obj.dLdB = sum(gradOutput, 2);
            
            % Compute gradient of loss with respect to input
            dLdInput = obj.weights'*gradOutput;
            
            % Update weights and bias using gradient descent
            obj.weights = obj.weights - learningRate*obj.dLdW;
            obj.bias = obj.bias - learningRate*obj.dLdB;
        end
    end
end
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