Build Time delay neural network using Deep learning tool box

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I wanna build my own Deep neural network which accepts two inputs and estimate two outputs. The input signals of the first layer are formed by tapped delay lines to consider the memory effect. I can design my network using (Time delay neural network), but I can't find the leaky rectified linear unit (Relu) activation function or use Adam as an optimization algorithm in such type of networks (Time delay neural network).
Now I wanna use Deep neural network toolbox to design this model with the MSE loss function and Adam as the optimizer with a mini-batch size of 256. The activation function is the leaky rectified linear unit (ReLU) with a slope of 0.01 for negative input. Any recommendation how to build such model?

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