Why IIR Filters Become Unstable in Fixed-Point DSP Systems

Introduction Infinite Impulse Response (IIR) filters are the workhorses of real-time DSP systems. They offer superior frequency selectivity with fewer coefficients compared to FIR filters, making them ideal for resource-constrained embedded applications. However, every DSP engineer who has implemented IIR filters in fixed-point systems has encountered the dreaded instability: filters that work perfectly in floating-point simulation suddenly oscillate, saturate, or produce garbage output when deployed to hardware. This isn’t just academic—it’s a production-stopping problem that has derailed countless projects. The issue stems from the fundamental tension between IIR filters’ recursive nature and the limited precision of fixed-point arithmetic. In this article, we’ll dissect exactly why this happens and provide practical solutions you can implement today. ...

March 20, 2026 · 6 min · SignalForge

Why Spectral Leakage Misleads Tonal Detection in Real Signals

Introduction Every DSP engineer has faced this scenario: you implement a textbook FFT-based tone detector, validate it with synthetic signals, and watch it fail spectacularly when deployed on real-world data. The culprit? Spectral leakage – that subtle but devastating artifact that transforms clean frequency bins into misleading spectral smears. While spectral leakage is well-documented in theory, its practical impact on tonal detection systems is often underestimated until it causes false alarms, missed detections, or incorrect frequency measurements in production systems. ...

March 20, 2026 · 7 min · SignalForge