Signal processing

mic in a soundproof room

Many problems boil down to separating signal from noise, though what is “signal” and what is “noise” depends on context. One person’s signal is another person’s noise.

Noise might be something like random static, but it could also simply be something you’re not interested in at the time. Maybe you’d like to pick out the bass line from a recording, and in that moment you’d consider the piano to be noise. No offense to the person on piano.

Reducing and shifting noise

Maybe the noise itself is what you’re interested in because you want to control it. You might want to reduce it, or if that’s not possible, you might want to shift some of its spectrum to where it is less noticeable.

If we’re talking about literal noise, this is one of the primary tasks of psychoacoustics, but there are many cases where we’re interested in reducing “noise” in the more general sense of unwanted randomness.

Deliberately adding noise

Sometimes, rather than filter out noise, you might want to add noise into a system that doesn’t have enough noise because, counter-intuitively, noise can sometimes make a system more reliable. For example, sometimes a little noise can get a Kalman filter unstuck. Also, it’s often useful to add just enough noise to data to protect privacy.

Help with signal processing

We have experience helping companies like yours with signal processing.

Brian Beckman “John helped us solve a vexing and festering problem. Reducing it to mathematics and then to code required educated guesses, creative assumptions, intuition, deep knowledge of digital signal processing, and shots in the dark. This is where John excels: just the right mix of practical urgency with mathematical rigor. It’s difficult to overemphasize the difficulty of this problem and the acumen required to solve it completely and on a schedule. Just fantastic!” — Brian Beckman, PhD

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Amazon, Facebook, Google, US Army Corp of Engineers, Amgen, Microsoft, Hitachi Data Systems