Build a Native DASYLab Hampel Filter: Robust Spike Removal with MAD

Build a native Hampel filter for DASYLab with AI-assisted C++ development. Follow the numerical contract, independent GNU GSL and Python references, frozen tests, bounded streaming, native Toolkit integration, and selected real-host measurements. The host demonstrations replay synthetic signals in DASYLab 2026 English. A Hampel flag identifies a candidate anomaly, not a confirmed sensor fault. Keep the raw signal. This is a development documentary, not a claim of complete product acceptance. Historical checkpoints keep their dated findings; later host evidence follows in Chapter 8. Remaining acceptance limits are explained in Chapter 9. English narration: AI-generated Sarah voice. English, German and Russian subtitles. CHAPTERS 00:00 Introduction: Why selective spike removal? 01:04 1: Agree on the Behavior 02:15 2: Understand Median and MAD 03:27 3: Establish an Independent Reference 04:42 4: Freeze Reproducible Tests 05:54 5: Build the Shared Core 07:08 6: Process a Stream Correctly 08:53 7: Integrate the Native Module 21:13 8: Challenge the Live Result 28:37 9: Review Evidence and Limits REFERENCE GNU Scientific Library: https://www.gnu.org/software/gsl/ SERIES    • Build DASYLab Extensions with AI   PREVIOUS EPISODES Foundation:    • Build Native DASYLab Extensions with AI - ...   4253H filter:    • 4253H in DASYLab: Native AI-Built Filter, ...   CHANNEL    / @dasylabaicoding