Quantitative Verification: Proving Filter Performance in Noisy DSP Systems
Introduction In many DSP workflows, filter performance is judged visually: a before/after spectrum plot a response curve screenshot a cleaned-looking waveform While useful for intuition, visual inspection is not engineering verification. In noisy systems, subjective evaluation often hides: incomplete suppression signal distortion unstable behavior regression drift This article explains how quantitative verification transforms filter design from guesswork into provable engineering outcomes. The Problem With “Looks Clean” Evaluation Human perception is poor at judging: ...