Updated: Apr 5, 2022
Capturing a digitally converted audio signal may reproduce cumulative impulse divergences at a consistent bit rate. This divergence is NOT quantized dimensionally and may result in signal loudness, clipping, and frequency saturation.
Recorded Source: https://www.youtube.com/watch?v=QCKL95HAdQ8 - Itzhak Perlman - Philadelphia Symphony - P. I. Tchaikovsky - Violin Concerto in D major
Experiencing the difference!
“Can you mitigate the blending resolution of low frequency instruments? Can you identify the fluttering clarity of wind instruments from the bowed vibrato of stringed instruments? Are the high notes piercing and low notes dull? Can you differentiate the attack on a 2-dimensional percussive instrument from the plucking of a 1-dimenisonal stringed instrument? ”
Although the audible range for human hearing is constrained between 20Hz and 20kHz, humans can discern and register a sophisticated combinatoric variation of simultaneously layered frequencies and granular intensities.
The Art of Perfecting Audio Reality
An analog audio signal consists of an infinite number of infinitesimal amplitude points along its wavelength. Digital audio technologies calibrate distinct time intervals to encoded audio amplitudes. Regardless of the recording sample-rate and transfer bitrate, digitally converted audio signals loose dynamic floating-point resolution. This missing data creates aliasing, and audio saturation. Our technology reconstructs missing floating-point data by converting digital signals into renormalized Quantum Dimensional time-dependent functions.
Our demonstration reveals the refining capabilities of attenuating topological dimensional aspects of audio. At 4kHz, we can easily identify the texture, attack, delay, and decay of diverse instruments hidden in layers of obscurity.