Query regarding neural network model
To debug this case, I suggest you try the following steps:


Reduce the features step-by-step until you end up with using just 1 feature and see whether the accuracy changes or not.
Add a sine-wave and a random noise to the feature set and see whether it effects any of these optimization algorithms.
Re-evaluate how you selected or derived these features, check if these are highly correlated.
Are your classification targets highly imbalanced? If so, then under/over sample them to achieve a more balanced training set. Then check the performance of you algorithm after training over this balanced dataset.


As already highlighted by Jan van der Vegt, its extremely odd that changing the no of features from 8 to 40 has no impact on test set accuracy.