---
title: "Ten Little Algorithms, Part 5: Quadratic Extremum Interpolation and Chandrupatla's Method"
url: https://daily.dev/posts/ten-little-algorithms-part-5-quadratic-extremum-interpolation-and-chandrupatla-s-method-gm9mcdxvh
source_url: https://www.embeddedrelated.com/showarticle/855.php
type: article
source: "EmbeddedRelated"
published: 2026-05-31T07:48:20.877Z
updated: 2026-05-31T09:30:10.255Z
tags: ["python", "embedded"]
reading_time: 21
upvotes: 0
comments: 0
language: en
---

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# Ten Little Algorithms, Part 5: Quadratic Extremum Interpolation and Chandrupatla's Method

**[EmbeddedRelated](https://daily.dev/sources/embeddedrelated)** · 21 min read · 0 upvotes · 0 comments

## Summary

Two compact numerical algorithms are explored for embedded and scientific computing: quadratic extremum interpolation and Chandrupatla's root-finding method. Quadratic interpolation fits a parabola to three sampled points around a waveform peak, achieving cubic error scaling with timestep — a significant improvement over the quadratic scaling of raw sample maxima. The technique requires smooth, well-sampled data to work reliably. Chandrupatla's 1997 method is presented as a simpler alternative to Brent's method for bracketed root-finding, combining bisection with inverse quadratic interpolation using a straightforward switching criterion. Python implementations and convergence comparisons against scipy's brentq are provided, showing Chandrupatla converges comparably or faster on flat/multiple-root functions.

## Full article

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---

Tags: [#python](https://daily.dev/tags/python), [#embedded](https://daily.dev/tags/embedded)

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