I aim to decrease the Mean Squared Error (MSE) in my model. Currently, the MSE stands at 0.21, but I’m targeting a value around 0.002342. My goal is to accurately predict the path, delay, Doppler shift, and gain. However, despite these parameters, my predictions are inaccurate.

I’m utilizing TensorFlow’s Functional API to predict four parameters. My input data consists of complex numbers with a size of 10000x9x8, and my label data also comprises complex numbers with a size of 10000×7. I’m using the ReLU activation function, Mean Squared Error (MSE) as the loss function, and the output is a linear function. Are there any boundary conditions I should include to ensure that the MSE is within the range of (10^{-3})? plz help me through out this what parameters should I use any boundary condition.