Number Theory for Codes
If CRCs have felt like black magic, this post peels back the curtain with basic number theory and polynomial arithmetic over GF(2). It shows how fixed-width processor arithmetic becomes arithmetic in a finite field, how bit sequences are treated as polynomials, and why primitive polynomials generate every nonzero element. You also get practical insights on CRC implementation with byte tables and LFSRs.
Ten Little Algorithms, Part 1: Russian Peasant Multiplication
Jason Sachs revisits a centuries-old multiplication trick and shows why it still matters. He lays out Russian Peasant Multiplication with simple Python code, then reveals how the same shift-and-add pattern maps to GF(2) polynomial arithmetic and to exponentiation by squaring. The post mixes historical context with practical bitwise techniques that are useful for embedded and low-level math work.
Second-Order Systems, Part I: Boing!!
Jason Sachs takes the spring 'boing' of a doorstop into the math of second-order systems, using the series LRC circuit as a concrete example. He shows two standard transfer-function forms, explains why ωn only scales time while ζ sets the response shape, and derives pole locations plus an exact overshoot formula that helps tune embedded-system responses.
Slew Rate Limiters: Nonlinear and Proud of It!
Slew-rate limits are a small nonlinear detail that often decides whether a controller behaves nicely or wrecks hardware. Jason Sachs walks through why slew limits appear in electronics and actuators, then shows two practical digital ways to impose limits: constraining input increments and constraining input around the output. He compares performance on underdamped second-order systems, gives closed-form intuition for overshoot, and demonstrates simulations with scipy and ODE solvers.
Bad Hash Functions and Other Stories: Trapped in a Cage of Irresponsibility and Garden Rakes
A tiny filename decision in MATLAB's publish() can silently swap rendered equations, and Jason Sachs shows why that matters. He reproduces the bug, walks through hash-function basics and collision math, and contrasts safe and unsafe caching strategies. The piece then broadens into practical lessons about software fringes, legacy constraints, and the usability traps that leave engineers repeatedly stumbling over avoidable design choices.
How to Estimate Encoder Velocity Without Making Stupid Mistakes: Part II (Tracking Loops and PLLs)
Jason Sachs explains why simple differentiation of encoder counts often fails and how tracking loops and PLLs give more robust velocity estimates. Using a pendulum thought experiment and Python examples, he shows how a PI-based tracking loop reduces noise and eliminates steady-state ramp error, and why vector PLLs with quadrature mixing avoid cycle slips and atan2 unwrap pitfalls in noisy or analog sensing.
Fluxions for Fun and Profit: Euler, Trapezoidal, Verlet, or Runge-Kutta?
Which ODE solver should you pick for resource‑constrained embedded simulations? Jason Sachs walks through practical numerical methods — Euler, trapezoidal, midpoint, 4th‑order Runge‑Kutta, semi‑implicit Euler, Verlet and the Forest–Ruth symplectic scheme — using hands‑on examples (damped bead, Kepler orbit, pendulum). He highlights accuracy vs. function‑evaluation cost, timestep guidance, and why symplectic methods beat general solvers for long‑term energy conservation.
Chebyshev Approximation and How It Can Help You Save Money, Win Friends, and Influence People
Are expensive math libraries or huge lookup tables eating CPU and flash on your microcontroller? In this practical guide Jason Sachs shows how Chebyshev polynomial approximation (with range reduction, splitting, and small interpolated tables) can give near-minimax accuracy while using far less code and runtime. The post compares Taylor series, plain and interpolated tables, and explains how to fit empirical sensor data and evaluate coefficients efficiently.
Polynomial Math
This post walks through squaring and inversion in a tiny finite field to make ECC math tangible. Using GF(2^5) with primitive polynomial beta^5 + beta^2 + 1 it shows why squaring cancels cross terms so you only need half the lookup table, and how Fermat exponentiation computes inverses via repeated squarings and multiplies. It also demonstrates the Extended Euclid polynomial inverse and compares FPGA and CPU tradeoffs.
Elliptic Curve Cryptography - Multiple Signatures
Point pairings let you compress many independent elliptic-curve signatures into a single verification, reducing n checks to one. This post explains how each signer derives a coefficient from the ordered list of public keys, aggregates signatures on the base group and public keys on the extension group, and verifies everything with one pairing computation. It also flags practical cautions like key validation and agreed ordering.
Bad Hash Functions and Other Stories: Trapped in a Cage of Irresponsibility and Garden Rakes
A tiny filename decision in MATLAB's publish() can silently swap rendered equations, and Jason Sachs shows why that matters. He reproduces the bug, walks through hash-function basics and collision math, and contrasts safe and unsafe caching strategies. The piece then broadens into practical lessons about software fringes, legacy constraints, and the usability traps that leave engineers repeatedly stumbling over avoidable design choices.
Linear Regression with Evenly-Spaced Abscissae
Jason Sachs cuts through the matrix algebra to show a tiny trick for linear regression when x values are evenly spaced. You can compute the intercept as the mean and the slope as a simple weighted sum with arithmetic weights, using q = 12/(m^3 - m). The post includes Python examples and a compact routine to get least-squares coefficients without matrix solvers.
Quaternions and the spatial rotations in motion enabled wearable devices. Exploiting the potential of smart IMUs attitude estimation.
Have you always wondered what a quaternion is? this is your post. Attitude or spatial orientation analysis is a powerful element in wearable devices (and many other systems). Commercially available sensors can provide this information out-of-the-box without requiring complex additional implementation of sensor fusion algorithms. Since these are already on-chip solutions devices can serve as a way to explore and analyze motion in several use cases. Mathematical analysis for processing quaternion is presented along with a brief introduction to them, Although they are not really easy to visualise, a couple fairly simple examples are provided which may allow you to gain some intuition on what's the logic behind them.
A Second Look at Slew Rate Limiters
Picking the right slew rate can cut overshoot dramatically while keeping delay reasonable, Jason shows. He numerically analyzes a feedforward slew-rate-limited step into a normalized second-order system and proposes a simple empirical rule R = Δx/(2π α τ) with α ≈ 1. The post includes Python/Scipy code and a 3→5 V example that demonstrates about a 3× overshoot reduction and a ≈5τ peak delay.
How to Succeed in Motor Control: Olaus Magnus, Donald Rumsfeld, and YouTube
Jason Sachs turned frustration with algorithm-heavy motor-control app notes into a practical MASTERs class, now available on YouTube. He walks through building a fifteen-minute field-oriented control refresher, the hazards teams commonly miss, and the months of prep required to make a polished technical lecture. Read for a candid behind-the-scenes look at teaching motor control to engineers and tips you can apply to your next drive project.
Shibboleths: The Perils of Voiceless Sibilant Fricatives, Idiot Lights, and Other Binary-Outcome Tests
Binary tests look simple until you try to pick a threshold, because false positives, false negatives, and base rate all collide. Jason Sachs uses a deliberately absurd detective story, then walks through the math of expected value, medical screening tradeoffs, idiot lights, and even a triage-style three-way decision. The payoff is a practical way to think about when a pass/fail signal helps, and when raw data or a second test is worth the extra complexity.
Linear Feedback Shift Registers for the Uninitiated, Part IX: Decimation, Trace Parity, and Cyclotomic Cosets
Taking every jth bit of a maximal-length LFSR uncovers a surprising algebraic structure. Jason Sachs walks through cyclotomic cosets, shows why decimation by powers of two preserves minimal polynomials, and connects LFSR output to trace parity and simple bitmask parity computations. The article uses hands-on Python with libgf2, Berlekamp-Massey, and state recovery so you can reproduce and automate these analyses.
Elliptic Curve Cryptography - Security Considerations
The security of elliptic curve cryptography is determined by the elliptic curve discrete log problem. This article explains what that means. A comparison with real number logarithm and modular arithmetic gives context for why it is called a log problem.
A Second Look at Slew Rate Limiters
Picking the right slew rate can cut overshoot dramatically while keeping delay reasonable, Jason shows. He numerically analyzes a feedforward slew-rate-limited step into a normalized second-order system and proposes a simple empirical rule R = Δx/(2π α τ) with α ≈ 1. The post includes Python/Scipy code and a 3→5 V example that demonstrates about a 3× overshoot reduction and a ≈5τ peak delay.
Polynomial Math
This post walks through squaring and inversion in a tiny finite field to make ECC math tangible. Using GF(2^5) with primitive polynomial beta^5 + beta^2 + 1 it shows why squaring cancels cross terms so you only need half the lookup table, and how Fermat exponentiation computes inverses via repeated squarings and multiplies. It also demonstrates the Extended Euclid polynomial inverse and compares FPGA and CPU tradeoffs.
Elliptic Curve Cryptography - Extension Fields
An introduction to the pairing of points on elliptic curves. Point pairing normally requires curves over an extension field because the structure of an elliptic curve has two independent sets of points if it is large enough. The rules of pairings are described in a general way to show they can be useful for verification purposes.
Quaternions and the spatial rotations in motion enabled wearable devices. Exploiting the potential of smart IMUs attitude estimation.
Have you always wondered what a quaternion is? this is your post. Attitude or spatial orientation analysis is a powerful element in wearable devices (and many other systems). Commercially available sensors can provide this information out-of-the-box without requiring complex additional implementation of sensor fusion algorithms. Since these are already on-chip solutions devices can serve as a way to explore and analyze motion in several use cases. Mathematical analysis for processing quaternion is presented along with a brief introduction to them, Although they are not really easy to visualise, a couple fairly simple examples are provided which may allow you to gain some intuition on what's the logic behind them.
Elliptic Curve Cryptography - Multiple Signatures
Point pairings let you compress many independent elliptic-curve signatures into a single verification, reducing n checks to one. This post explains how each signer derives a coefficient from the ordered list of public keys, aggregates signatures on the base group and public keys on the extension group, and verifies everything with one pairing computation. It also flags practical cautions like key validation and agreed ordering.
Monte Carlo Integration
Monte Carlo integration looks deceptively simple, estimate an area by throwing random points at it and counting hits. Jason Sachs uses that idea to approximate pi, compare error scaling, and then show why the same approach becomes far more useful in higher dimensions. He also demonstrates a stratified sampling trick that improves accuracy by spending samples where they matter most.
