http://www.mix-engineer.com/audio-philosophy/digital-vs-analog-mixing/
'' Fixed point systems use the 32 bits in the conventional way, to provide an internal dynamic range of about 192dB. Systems that use fixed 32 bit processing (like the Yamaha desks)usually arrange for the original 24 bit audio signal to sit roughly in the middle of that 32 bit processing number to provide a lower noise floor and slightly greater headroom for the signal processing. BTW 192 dB SPL is roughly equivalent to two atmospheres pressure onthe compression of the wave and a complete vacuum on the rarefaction.
Floating point systems still use 32 bit numbers, but organise them differently. Essentially, they keep the 24 bit resolution for the audio signal, but use the remaining bits to denote a scaling factor. In other words the 24 bit resolution can be cranked up or down within a collosal internal dynamic range so that, in effect, you can never run out of headroom or fall into the noise floor -- there is something like 1500dB of dynamic range within the processing, if the maths is done properly.
Most high end consoles and workstations employ floating point maths because (if done properly) you can get better performance and quality inthe computations. Most budget/low end consoles and DAWs use fixed point processing because its easier and faster, and can be implemented in hardware more easily.
Cool Edit Pro simply converts the 16-bit data into a 32-bit float format on the way in, so that any calculations you do (EQ, gain changes, effects, etc.) have smaller cumulative errors. Simply put, if you're going to do lots of work on an audio file, the final result will sound cleaner if you give it more bits of resolution, even if you end up saving it as a 16-bit file at the end. This is the same reason that Wavelab offers 24-bit and 32-bit temporary files, even when working with 16-bit audio.''
http://www.analog.com/en/content/Fixed-Point_vs_Floating-Point_DSP/fca.html
Dynamic Range and Precision
The exponentiation inherent in floating-point computation assures a much larger
dynamic range – the largest and smallest numbers that can be represented - which is especially important when processing extremely large data sets or data sets where the range may be unpredictable. As such, floating-point processors are ideally suited for computationally intensive applications.
It is also important to consider fixed and floating-point formats in the context of precision – the size of the gaps between numbers. Every time a DSP generates a new number via a mathematical calculation, that number must be rounded to the nearest value that can be stored via the format in use. Rounding and/or truncating numbers during signal processing naturally yields quantization error or ‘noise’ - the deviation between actual analog values and quantized digital values. Since the gaps between adjacent numbers can be much larger with fixed-point processing when compared to floating-point processing, round-off error can be much more pronounced. As such, floating-point processing yields much greater precision than fixed-point processing, distinguishing floating-point processors as the ideal DSP when computational accuracy is a critical requirement.
http://www.tomshardware.co.uk/forum/46221-6-floating-point-fixed-point-calculation
From what I've been reading, (The Art of Digital Audio, Mastering
> Audio, and Greg Duckett's "Superior Audio Requires Fixed-Point DSPs"
> on Rane's website), there appears to be little doubt that as far as
> audio is concerned,
fixed point calculations are superior to floating
> point calculations. 32-bit floating point predominates in our industry
> (Protools, Nuendo, DP, etc) because the calculations are cheaper to
> achieve from ready-made chips. Fixed point calculations are superior
> (i.e., more accurate), leave nothing for the chip to assume, but have
> *a lot* more work involved from the developer's point of view.
????
http://www.gearslutz.com/board/so-m...2bit-floating-point-vs-32bit-fixed-point.html
http://www.recordingmag.com/resources/resourceDetail/377.html
''We won’t get into this distinction here; certain operations benefit from fixed point math and others from floating point, with respect to accuracy and speed on different computers. More bits in your data path will almost always help you; fixed vs. floating point may or may not.''
http://www.audioecstasyproductions.com/pdfs/bitsample.pdf
http://mixonline.com/mag/audio_im_sixty_four/
http://www.ti.com/lit/wp/spry061/spry061.pdf
http://elsi-ing.pagespro-orange.fr/docs/rane%20fixed%20vs%20floating%20point%20note153.pdf
http://dsp-book.narod.ru/soundproc.pdf