Errata for the book: 'Understanding Digital Signal Processing'
Rick Lyons collects all errata for every edition and printing of his book Understanding Digital Signal Processing into one centralized list, with downloadable PDFs for each variant. The post also shows how to identify your book's printing number for American 1st, 2nd, and 3rd editions and flags a few oddball versions that lack errata.
Feedback Controllers - Making Hardware with Firmware. Part 3. Sampled Data Aspects
This article digs into practical sampled-data issues you must address when building feedback controllers for circuit emulation. It highlights a common MATLAB versus Simulink discrepancy caused by DAC holding, explains why FOH (ramp-invariant) c2d conversion matters, and surveys latency, bit depth, filter and precision trade-offs. It also lists candidate ADCs, DACs and FPGAs used in a real evaluation platform to guide hardware choices.
Finally got a drone!
Stephane Boucher finally bought a DJI Phantom 4 and found it does more than boost his video production value, it’s also hugely fun to fly. He used the drone for an aerial shot at SEGGER’s anniversary and for a beach project where kids drew a turtle while a separate camera captured a side timelapse. The post highlights creative shot combinations and a reminder to fly where it is legal.
Feedback Controllers - Making Hardware with Firmware. Part 2. Ideal Model Examples
An engineer's guide to building ideal continuous-time models for hardware emulation, using TINA Spice, MATLAB and Simulink to validate controller and circuit behavior. The article shows how a passive R-C network can be emulated by an amplifier, a current measurement and a summer, with Spice, MATLAB and Simulink producing coincident Bode responses. Small phase differences between MATLAB and Simulink are noted, and sampled-data issues are slated for the next installment.
Feedback Controllers - Making Hardware with Firmware. Part I. Introduction
This first post kicks off a series on using DSP and feedback control with mixed-signal electronics and FPGAs to emulate two-terminal circuits and create low latency controllers. It frames circuit emulation as a feedback problem, highlights latency as the key practical constraint, and outlines the planned evaluation hardware, target devices, and software tools that will be used in later MATLAB/Simulink and FPGA work.
Exact Near Instantaneous Frequency Formulas Best at Zero Crossings
Cedron Dawg derives time-domain formulas that yield near-instantaneous frequency estimates optimized for zero crossings of pure tones. Complementing his earlier peak-optimized results, these difference-ratio formulas work for real and complex signals, produce four-sample estimators similar to Turners, and cancel amplitude terms, making them attractive low-latency options for clean tones while warning they degrade in noise and at peaks.
SEGGER's 25th Anniversary Video
Stephane Boucher spent a week at SEGGER's headquarters and distilled that visit into a tight, two-minute 25th anniversary video. The post highlights rising production value, thanks to softbox lighting and a two-camera setup that allows seamless wide-to-tight cuts and emotional close-ups. Stephane invites readers to watch full screen, leave feedback and thumbs-up on YouTube, and suggests future coverage like product launches or companies with happy engineers.
Above-Average Smoothing of Impulsive Noise
This post introduces a smoothing trick that behaves a lot like a moving average for high-frequency noise, but does a much better job of suppressing impulsive spikes. Rick Lyons shows how the corrected average is computed from the sample count, the sample imbalance around the mean, and the total deviation. He also compares the method against a standard moving average on a noisy step signal, where the improvement is easy to see.
Went 280km/h (174mph) in a Porsche Panamera in Germany!
A week at SEGGER’s headquarters in Germany turned into more than a video shoot, it became a look inside a company that clearly runs on passion, trust, and a lot of teamwork. Stephane Boucher also gets an unforgettable autobahn ride in a Porsche Panamera, hitting 280 km/h along the way. Between interviews, B-roll, and a 25th anniversary celebration, he comes away impressed by both the people and the pace.
Looking For a Second Toolbox? This One's For Sale
A battered blue toolbox once used by Steve Wozniak during Apple’s early days is now up for auction, complete with a self-adhesive label bearing his name. Rick Lyons notes the 13 x 7 x 5 inch steel box shows heavy wear and includes a three-section lid tray, it currently resides in Italy and is listed with an estimated price around $25,000, shippable to buyers.
Find Aliased ADC or DAC Harmonics (with animation)
If a sinewave drives an ADC or DAC, device nonlinearities create harmonics that can fold back as aliases above Nyquist. This post shows a simple Matlab model, using an NCO, a static nonlinearity, and a DFT to generate spectra and reveal aliased harmonics, with animated illustrations to make aliasing intuitive. The approach works for both ADC and DAC measurement setups and highlights realistic effects like quantization noise.
DFT Bin Value Formulas for Pure Real Tones
Cedron Dawg derives a closed-form expression for the DFT bin values produced by a pure real sinusoid, then uses that formula to explain well known DFT behaviors. The post walks through the algebra from Euler identities to a compact computational form, highlights the integer versus non-integer frequency cases, and verifies the result with C code and printed numeric output.
Modelling a Noisy Communication Signal in MATLAB for the Analog to Digital Conversion Process
Practical signal modeling treats receiver noise as a fixed power source, not something tied to the transmitted waveform. Parth demonstrates why using MATLAB's awgn(sig,SNR,'measured') can misrepresent an analog front end and provides a short function that scales your signal so the added AWGN produces the desired receiver noise variance. This prepares realistic inputs for upcoming ADC simulations.
Plotting Discrete-Time Signals
Neil Robertson demonstrates a practical interpolate-by-8 FIR approach to make sampled signals look like their continuous-time counterparts when plotted. The post explains a 121-tap filter designed for signals up to 0.4*fs, shows Matlab examples for a sinusoid and a filtered pulse, and highlights the transient and design trade-offs so you can reproduce clean plots with the supplied interp_by_8.m code.
Generating pink noise
This post implements a stochastic Voss-McCartney pink-noise generator in Python, tackling why incremental per-sample algorithms do not map well to NumPy batch operations. It presents a practical NumPy/Pandas approach that uses geometric-distributed update events and pandas' fillna for column-wise zero-order hold to make batch generation efficient. The generated noise shows a power-spectrum slope near -1, matching expected 1/f behavior.
Two Easy Ways To Test Multistage CIC Decimation Filters
Rick Lyons shows that you can validate multistage CIC decimation filters with just two obvious tests, no elaborate spectral setup required. Apply a unit-sample impulse to check a combinatorial yout(1) value when D ≥ S, or feed an all-ones step to confirm an S-sample transient followed by a DS steady state; the Appendix ties both checks to Pascal's triangle and binomial math.
Fitting a Damped Sine Wave
Detlef Amberg presents a simple linear-algebra approach to recover frequency, phase, amplitude, and damping of a sampled damped sine wave. Instead of nonlinear fitting, the method casts the waveform as a second-order difference equation, uses linear regression to estimate b and omega, and recovers amplitude and phase by mixing with quadrature carriers; amplitude and damping are then fine-tuned with a gradient iteration. MATLAB code is available on File Exchange.
A Fast Real-Time Trapezoidal Rule Integrator
Rick Lyons presents a compact, recursive real-time Trapezoidal Rule integrator that computes N-sample discrete integration using only four arithmetic operations per input sample. The proposed network yields a finite-length, linear-phase impulse response with constant group delay (N-1)/2 and cuts substantial computation compared with a tapped-delay implementation, making it useful for speeding Romberg-based digital filters.
Exponential Smoothing with a Wrinkle
Cedron Dawg shows how pairing forward and backward exponential smoothing produces exact, frequency-dependent dampening for sinusoids while canceling time-domain lag. The average of the two passes scales the tone by a closed-form factor, and their difference acts like a first-derivative with a quarter-cycle phase shift. The post derives the analytic dampening formulas, compares them to the derivative, and includes a Python demo for DFT preprocessing.
Adaptive Beamforming is like Squeezing a Water Balloon
Think of adaptive beamforming as squeezing a water balloon, a simple analogy that reveals how combining multiple antennas creates focused gains and deep nulls. This post walks through the MVDR (Wiener-filter–based) solution, explains steering and scanning vectors, and shows how array geometry and known signal direction control what you can and cannot cancel. Practical tips highlight limits like the N-1 interferer rule.
Exact Frequency Formula for a Pure Real Tone in a DFT
Cedron Dawg derives an exact closed form formula to recover the frequency of a pure real sinusoid from three DFT bins, challenging the usual teaching that it is impossible. The derivation solves for cos(alpha) in a bilinear form and gives a computationally efficient implementation (eq.19), with practical notes on implicit Hann-like weighting and choosing the peak bin for robustness.
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 Fast Real-Time Trapezoidal Rule Integrator
Rick Lyons presents a compact, recursive real-time Trapezoidal Rule integrator that computes N-sample discrete integration using only four arithmetic operations per input sample. The proposed network yields a finite-length, linear-phase impulse response with constant group delay (N-1)/2 and cuts substantial computation compared with a tapped-delay implementation, making it useful for speeding Romberg-based digital filters.
ADC Clock Jitter Model, Part 2 – Random Jitter
Neil Robertson shows how to simulate ADC sample-clock random jitter in Matlab, moving from band-limited Gaussian noise to wideband and close-in phase noise. The post highlights practical artifacts such as aliasing of wideband clock noise, the 20*log10 dependence of jitter sidebands on input frequency, and why cubic interpolation plus a custom noise_filter produces accurate rms and spectral results engineers can trust.
A Brief Introduction To Romberg Integration
Romberg integration delivers dramatic accuracy gains for definite integrals by combining multiple trapezoidal approximations into a single highly accurate result. Rick Lyons demonstrates how just five samples can achieve 0.0038% error versus a trapezoidal rule needing 100 samples, and a 17-sample example hits 3.6×10−4% error. The post outlines the N-segment procedure, cost scaling, and links to MATLAB code.
A Fast Guaranteed-Stable Sliding DFT Algorithm
Rick Lyons presents a compact, computationally efficient sliding DFT that computes a single N-point DFT bin output for each input sample in real time. The design replaces the traditional complex resonator with a 2nd-order real resonator and uses pole/zero cancellation to match the DFT bin response. Crucially, the resonator poles remain on the z-plane unit circle even with quantized coefficients, guaranteeing numerical stability.
Learn to Use the Discrete Fourier Transform
Discrete-time sequences arise in many ways: a sequence could be a signal captured by an analog-to-digital converter; a series of measurements; a signal generated by a digital modulator; or simply the coefficients of a digital filter. We may wish to know the frequency spectrum of any of these sequences. The most-used tool to accomplish this is the Discrete Fourier Transform (DFT), which computes the discrete frequency spectrum of a discrete-time sequence. The DFT is easily calculated using software, but applying it successfully can be challenging. This article provides Matlab examples of some techniques you can use to obtain useful DFT’s.
Going back to Germany!
A conference conversation turned into a return trip to Germany for Stephane Boucher, this time to visit SEGGER’s headquarters in Dusseldorf and produce videos. The post shares how a chance introduction at ESC Boston led to the invitation, and it teases coverage from SEGGER’s 25th anniversary celebration. He also invites local tips and customer questions before the trip.
A New Contender in the Digital Differentiator Race
Rick Lyons presents a compact FIR differentiator that widens the usable linear-frequency range while remaining simple to implement. The five-tap impulse response boosts the linear operating band by roughly 33% over his earlier design, offers exact two-sample group delay and linear phase, and can be realized in a folded multiplier-free form using binary right shifts. The design targets signals below pi/2 radians per sample.
Multiplierless Exponential Averaging
Rick Lyons shows how to implement exponential averaging without multiplies by exploiting a rearranged leaky-integrator form and binary shifts. He demonstrates reducing the standard two-multiply averager to a single-multiply form, then eliminating the multiply entirely when the weighting α equals reciprocals or differences of reciprocals of powers of two. The post catalogs practical α choices for fixed-point filters and flags quantization as an open issue.
