Ten Little Algorithms, Part 6: Green’s Theorem and Swept-Area Detection
Jason shows how Green's Theorem becomes a practical, low-cost method to detect real-time rotation from two orthogonal sensors by accumulating swept area. The post derives a compact discrete integrator S[n] = S[n-1] + (x[n]*(y[n]-y[n-1]) - y[n]*(x[n]-x[n-1]))/2, compares integer and floating implementations, and analyzes noise scaling and sampling rate tradeoffs. Includes Python demos and threshold guidance.
Data Types for Control & DSP
Control engineers often default to double precision, but Tim Wescott shows that choice can waste CPU cycles on embedded targets. He separates numeric representation into floating point, integer, and fixed-point, then walks through the tradeoffs, including quantization, overflow, and performance. A concrete PID example highlights why integrator precision and ADC scaling should drive your choice of data type rather than habit.
Ten Little Algorithms, Part 5: Quadratic Extremum Interpolation and Chandrupatla's Method
Today we will be drifting back into the topic of numerical methods, and look at an algorithm that takes in a series of discretely-sampled data points, and estimates the maximum value of the waveform they were sampled from.
Ten Little Algorithms, Part 3: Welford's Method (and Friends)
Jason Sachs takes a practical look at Welford's method, a numerically stable online algorithm for computing mean and sample variance without storing large batches. He demonstrates Python implementations, shows why the naive sum and sum-of-squares approach suffers catastrophic cancellation, and why Welford is a better fit for memory- and CPU-constrained embedded systems. Jason then turns Welford into simple filters for tracking time-varying noise and discusses heuristic fixes and tradeoffs.
Python Code from My Articles Now Online in IPython Notebooks
Jason M. Sachs has published the Python code from his EmbeddedRelated articles as standalone IPython notebooks. He automated extraction of example code and pushed the notebooks to a public Bitbucket repository under the Apache license, and they are viewable via nbviewer. The post lists available notebooks and asks readers to link back to EmbeddedRelated and share feedback on how they used the code.
Ten Little Algorithms, Part 2: The Single-Pole Low-Pass Filter
Jason Sachs shows how a single-pole IIR low-pass filter, implementable in one line y += alpha * (x - y), tames noise in embedded signals without floating point. The post explains how to compute alpha from tau and delta-t, practical tradeoffs like phase lag and oversampling, and fixed-point pitfalls including how many extra state bits you need to avoid quantization. Short, practical, and code-ready.
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.
OOKLONE: a cheap RF 433.92MHz OOK frame cloner
Fabien Le Mentec built a pocket device that listens to and clones 433.92MHz OOK frames, automating the tedious reverse engineering of cheap wireless outlets. The prototype uses a Moteino with an RFM69 to sample demodulated OOK data, stores pulse durations in SRAM, and replays frames; the code and hardware notes are available on GitHub along with limitations and next steps.
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.
Signal Processing Contest in Python (PREVIEW): The Worst Encoder in the World
Jason Sachs previews a hands-on Python contest to find the best velocity estimator for a noisy, low-cost quadrature encoder. The post explains the Estimator API, submission constraints, and a 5 second, 10 kHz evaluation harness that uses a simulated "Lucky Wheel" encoder with realistic manufacturing timing errors. Jason also includes a simple baseline estimator and discusses the practical tradeoff between noise reduction and phase lag in velocity estimation.
How to Implement Image Processing Algorithms in FPGA Hardware
Recognized for their parallelism and reconfigurability, FPGAs prove ideal for real-time processing in medical imaging and computer vision. The step-by-step approach starts with understanding FPGA basics, emphasizing their reconfigurable nature and parallel processing. It guides users in algorithm selection based on factors like processing speed, resource utilization, and adaptability, then highlights designing modular and scalable algorithms. The process includes simulation for verification, synthesis using tools like Xilinx Vivado and Intel Quartus Prime, interfacing with image sensors, and testing on real hardware. The conclusion underscores FPGA's advantages in image processing, presenting ongoing opportunities for innovation in diverse industries.
How to Estimate Encoder Velocity Without Making Stupid Mistakes: Part I
Encoder velocity estimation is easy to get wrong, and Jason Sachs walks through the traps engineers fall into. He demolishes the common advice to time between encoder edges, shows how encoder quantization and state-width errors break that approach, and argues for fixed-rate sampling with sensible filtering for most control uses. Part II will cover more advanced estimators for higher performance needs.
OOKLONE: a cheap RF 433.92MHz OOK frame cloner
Fabien Le Mentec built a pocket device that listens to and clones 433.92MHz OOK frames, automating the tedious reverse engineering of cheap wireless outlets. The prototype uses a Moteino with an RFM69 to sample demodulated OOK data, stores pulse durations in SRAM, and replays frames; the code and hardware notes are available on GitHub along with limitations and next steps.
Signal Processing Contest in Python (PREVIEW): The Worst Encoder in the World
Jason Sachs previews a hands-on Python contest to find the best velocity estimator for a noisy, low-cost quadrature encoder. The post explains the Estimator API, submission constraints, and a 5 second, 10 kHz evaluation harness that uses a simulated "Lucky Wheel" encoder with realistic manufacturing timing errors. Jason also includes a simple baseline estimator and discusses the practical tradeoff between noise reduction and phase lag in velocity estimation.
Python Code from My Articles Now Online in IPython Notebooks
Jason M. Sachs has published the Python code from his EmbeddedRelated articles as standalone IPython notebooks. He automated extraction of example code and pushed the notebooks to a public Bitbucket repository under the Apache license, and they are viewable via nbviewer. The post lists available notebooks and asks readers to link back to EmbeddedRelated and share feedback on how they used the code.
Ten Little Algorithms, Part 6: Green’s Theorem and Swept-Area Detection
Jason shows how Green's Theorem becomes a practical, low-cost method to detect real-time rotation from two orthogonal sensors by accumulating swept area. The post derives a compact discrete integrator S[n] = S[n-1] + (x[n]*(y[n]-y[n-1]) - y[n]*(x[n]-x[n-1]))/2, compares integer and floating implementations, and analyzes noise scaling and sampling rate tradeoffs. Includes Python demos and threshold guidance.
Isolated Sigma-Delta Modulators, Rah Rah Rah!
Analog isolation can blow up DAQ budgets, but isolated sigma-delta modulators let you send a single 1-bit stream and a clock across the barrier, keeping costs down. Jason walks through Avago, TI, and Analog Devices parts, explains sigma-delta noise shaping in plain terms, and calls out the real engineering work: converting a 10–20 MHz bitstream into usable samples with sinc/CIC decimators or FPGA filtering.
Linear Feedback Shift Registers for the Uninitiated, Part XII: Spread-Spectrum Fundamentals
Jason Sachs shows why LFSR-generated pseudonoise is a natural fit for direct-sequence spread spectrum, then walks through Fourier basics, spectral plots, and runnable Python examples. The article demonstrates how DSSS multiplies a UART bitstream with a chipping sequence to spread energy, how despreading concentrates the desired signal while scrambling narrowband interference, and how multiple transmitters can share bandwidth when using uncorrelated sequences.
Linear Feedback Shift Registers for the Uninitiated, Part XIII: System Identification
Jason Sachs shows how the output of a linear feedback shift register can be used for active system identification, not just spread-spectrum testing. The article compares traditional sine-wave probing with LFSR-based PRBS methods, demonstrates a worked Ra-Rb-C example, and unpacks practical issues such as reflected pseudonoise, ADC quantization, sample counts, and noise-shaping tricks to improve estimates.
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.
Signal Processing Contest in Python (PREVIEW): The Worst Encoder in the World
Jason Sachs previews a hands-on Python contest to find the best velocity estimator for a noisy, low-cost quadrature encoder. The post explains the Estimator API, submission constraints, and a 5 second, 10 kHz evaluation harness that uses a simulated "Lucky Wheel" encoder with realistic manufacturing timing errors. Jason also includes a simple baseline estimator and discusses the practical tradeoff between noise reduction and phase lag in velocity estimation.
OOKLONE: a cheap RF 433.92MHz OOK frame cloner
Fabien Le Mentec built a pocket device that listens to and clones 433.92MHz OOK frames, automating the tedious reverse engineering of cheap wireless outlets. The prototype uses a Moteino with an RFM69 to sample demodulated OOK data, stores pulse durations in SRAM, and replays frames; the code and hardware notes are available on GitHub along with limitations and next steps.
Ten Little Algorithms, Part 6: Green’s Theorem and Swept-Area Detection
Jason shows how Green's Theorem becomes a practical, low-cost method to detect real-time rotation from two orthogonal sensors by accumulating swept area. The post derives a compact discrete integrator S[n] = S[n-1] + (x[n]*(y[n]-y[n-1]) - y[n]*(x[n]-x[n-1]))/2, compares integer and floating implementations, and analyzes noise scaling and sampling rate tradeoffs. Includes Python demos and threshold guidance.
Data Types for Control & DSP
Control engineers often default to double precision, but Tim Wescott shows that choice can waste CPU cycles on embedded targets. He separates numeric representation into floating point, integer, and fixed-point, then walks through the tradeoffs, including quantization, overflow, and performance. A concrete PID example highlights why integrator precision and ADC scaling should drive your choice of data type rather than habit.
Isolated Sigma-Delta Modulators, Rah Rah Rah!
Analog isolation can blow up DAQ budgets, but isolated sigma-delta modulators let you send a single 1-bit stream and a clock across the barrier, keeping costs down. Jason walks through Avago, TI, and Analog Devices parts, explains sigma-delta noise shaping in plain terms, and calls out the real engineering work: converting a 10–20 MHz bitstream into usable samples with sinc/CIC decimators or FPGA filtering.
Linear Feedback Shift Registers for the Uninitiated, Part XII: Spread-Spectrum Fundamentals
Jason Sachs shows why LFSR-generated pseudonoise is a natural fit for direct-sequence spread spectrum, then walks through Fourier basics, spectral plots, and runnable Python examples. The article demonstrates how DSSS multiplies a UART bitstream with a chipping sequence to spread energy, how despreading concentrates the desired signal while scrambling narrowband interference, and how multiple transmitters can share bandwidth when using uncorrelated sequences.
Linear Feedback Shift Registers for the Uninitiated, Part XIII: System Identification
Jason Sachs shows how the output of a linear feedback shift register can be used for active system identification, not just spread-spectrum testing. The article compares traditional sine-wave probing with LFSR-based PRBS methods, demonstrates a worked Ra-Rb-C example, and unpacks practical issues such as reflected pseudonoise, ADC quantization, sample counts, and noise-shaping tricks to improve estimates.
Modulation Alternatives for the Software Engineer
Jason starts with a hardware curiosity, the 7497 synchronous rate multiplier, and turns it into a practical lesson for firmware engineers. He contrasts conventional PWM with a simple accumulator-based method called "synthetic division," showing how it implements first-order delta-sigma behavior in software. The post explains when to pick PWM or delta-sigma and why the accumulator trick can give higher effective resolution at low update rates.
How to Implement Image Processing Algorithms in FPGA Hardware
Recognized for their parallelism and reconfigurability, FPGAs prove ideal for real-time processing in medical imaging and computer vision. The step-by-step approach starts with understanding FPGA basics, emphasizing their reconfigurable nature and parallel processing. It guides users in algorithm selection based on factors like processing speed, resource utilization, and adaptability, then highlights designing modular and scalable algorithms. The process includes simulation for verification, synthesis using tools like Xilinx Vivado and Intel Quartus Prime, interfacing with image sensors, and testing on real hardware. The conclusion underscores FPGA's advantages in image processing, presenting ongoing opportunities for innovation in diverse industries.
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.
