<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>DSP Automation on SignalForge Engineering Notes</title><link>https://blog.signal-forge.app/tags/dsp-automation/</link><description>Recent content in DSP Automation on SignalForge Engineering Notes</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 23 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.signal-forge.app/tags/dsp-automation/index.xml" rel="self" type="application/rss+xml"/><item><title>Why Automatic Filter Optimization Often Fails in Real DSP Systems</title><link>https://blog.signal-forge.app/posts/why-automatic-filter-optimization-fails/</link><pubDate>Mon, 23 Feb 2026 00:00:00 +0000</pubDate><guid>https://blog.signal-forge.app/posts/why-automatic-filter-optimization-fails/</guid><description>Automatic filter optimization promises optimal spectral results, but often fails in real systems. This article explains why engineering constraints and numerical stability break naive optimization approaches.</description></item></channel></rss>