I'm trying to get some intuition how digital noise due to quantization shows up in iir filters. I decided to do tests in C using Python to calculate psd and visualize. I've implemented Direct Form 1, 2, "Biquad" and "Low Noise" forms of realization of second-order iir filter from Matt's presentation. There is a typo in the "Low Noise Form" scheme - a1 and a2 gains should be switched. Other then that schemes correctly implement 2 order iir.
The input signal to each filter was a sine wave plus white noise with small amplitude x[n] = sin(2*pi*f*t[n]) + g*random( [-1, 1] ), g << 1, f=1kHz. Sampling frequency was 16384 Hz. All 4 forms implemented 2 order low-pass butterworth filter with cut-off frequency 0.2 Hz
x[n] = sin(2*pi*f*t[n]) + g*random( [-1, 1] ), g << 1, f=1kHz.
For g=1e-2 all implementations work fine. For g=1e-8 when quantization noise increases, all implementations give a lot of noise at low frequencies. I did not notice any significant difference between any of these implementations. I'll try to do more tests to figure out any difference in noise between the forms.
Quantization noise depends on the architecture of the processor, compiler and what not. But I do not think this can give a huge difference in results. We need to understand carefully digital noise during PSD estimation and all operations done at Matlab or Python.