The structure of this neural network consists of an input layer, a hidden layer, and an output layer. The network is configured to solve the XOR problem, with binary input values and a binary output. The hidden layer, represented by the array \texttt{hiddenLayer}, is connected to the inputs through weights \texttt{hiddenWeights}, while the output layer, \texttt{outputLayer}, is connected to the hidden layer via the weights \texttt{outputWeights}. The biases for each layer are initialized in \texttt{hiddenLayerBias} and \texttt{outputLayerBias}.
