Fractional Delay FIR Filters
You can realize arbitrary fractional-sample delays with standard FIR filters by shifting a sinc impulse response and removing symmetry, then windowing the result. This post shows a practical window-method implementation using Chebyshev windows, gives Matlab functions (frac_delay_fir.m and frac_delay_lpf.m) in the appendix, and walks through examples that demonstrate the delay, magnitude trade-offs, and how increasing taps widens the flat-delay bandwidth.
The DFT of Finite-Length Time-Reversed Sequences
Rick Lyons digs into a surprisingly under-documented corner of DSP, showing how finite-length time reversal changes a sequence's DFT. The post distinguishes flip and circular time-reversal, gives closed-form DFT relationships, and explains why modulo N arithmetic matters. Engineers get ready-to-use tables and derivations that clarify when and how time reversal affects spectral analysis.
Model Signal Impairments at Complex Baseband
Neil Robertson presents compact complex-baseband channel models for common signal impairments, implemented as short Matlab functions of up to seven lines. Using QAM examples and constellation plots, he demonstrates how interfering carriers, two-path multipath, sinusoidal phase noise, and Gaussian noise distort constellations and affect MER. The examples are lightweight and practical, making it easy to test receiver diagnostics and prototype adaptive-equalizer scenarios.
Update To: A Wide-Notch Comb Filter
Rick Lyons extends his earlier wide-notch comb filter work with a set of practical alternatives, including a linear-phase 3-RRS version and a dual 2-RRS structure. The post lays out the block diagrams, z-domain transfer functions, and MATLAB coefficients needed to model each option, then compares their frequency responses against the original design. It is a compact update for engineers who want more flexibility in notch width and realization style.
A Wide-Notch Comb Filter
Traditional comb filters make very narrow stopband notches, which limits their ability to suppress broader interfering tones. Rick Lyons presents a linear-phase comb filter that produces wider stopband notches than the conventional design while preserving linear-phase behavior. The post also reviews the traditional cascaded recursive running-sum architecture, its co-located dual poles and zeros on the z-plane, and the placement of nulls at integer multiples of fs/D.
An Efficient Lowpass Filter in Octave
Paul Lovell presents an efficient linear-phase lowpass FIR implemented in Octave, built as a Matrix IFIR with two matrix band-edge shaping stages followed by three recursive running-sum stages. The design reshapes input blocks into matrices to exploit interpolation structure and uses cumsum-based moving sums for speed. For a 200 Hz cutoff at 48 kHz the five-stage example ran about 15 times faster than a single-stage FIR.
Compute Modulation Error Ratio (MER) for QAM
Neil Robertson shows how to define and compute Modulation Error Ratio (MER) for QAM using a simplified baseband model and decision-slice errors. The post derives per-symbol and averaged MER formulas, explains when MER tracks carrier-to-noise ratio under AWGN and matched root-Nyquist filters, and provides example Pav values for QAM-16 and QAM-64 plus a Matlab script and practical tips.
Polynomial calculations on an FIR filter engine, part 1
FIR filter blocks can be repurposed as fast polynomial evaluators, offering hardware acceleration for non-linear compensation, function approximation, and harmonic synthesis, but they require careful scaling and coefficient management. This article outlines when to use binomial or fitted polynomials, compares Horner's nested evaluation with the direct power-sum approach, and highlights precision and overflow pitfalls on fixed-point engines like the Cypress DFB.
The Risk In Using Frequency Domain Curves To Evaluate Digital Integrator Performance
Frequency-response curves can be misleading when selecting a digital integrator, Rick Lyons shows, and he proves it with counterexamples using seven test signals. By comparing methods such as Simpson's 1/3 rule, Al-Alaoui, and Tick's rule on definite-integral tasks, Lyons demonstrates that a close match to the ideal frequency response does not guarantee accurate integrals, because input signal traits strongly affect results.
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.
Simulink-Simulation of SSB demodulation
This post walks through Simulink models that implement SSB demodulation and modulation, using Richard Lyons' phasing method as a foundation. It shows practical models for simple carrier multiplication and for the phasing method with cosine and -sin paths plus Hilbert filtering, and it highlights sampling, decimation, filter choices, and delay alignment to make the techniques work in simulation.
Wavelets II - Vanishing Moments and Spectral Factorization
This post walks through how vanishing moments turn into concrete algebraic constraints on wavelet filter coefficients, and why that leads to Daubechies filters. It explains how a wavelet with A vanishing moments is orthogonal to all polynomials up to degree A minus one, and it shows how those continuous conditions become discrete sums like sum_k k^n h1(k)=0. Expect clear links between approximation power and filter length.
Deesspee #5
Peter Kootsookos's Deesspee #5 is a very short micro-post simply titled "Computers". It acts as a minimalist flag in the Deesspee series pointing readers toward the computing topic on DSPRelated; click through to view the original entry and any context or discussion. This compact post is useful if you track the author's brief topic markers or short-format updates.
Accelerating Matlab DSP Code on the GPU
Seth Benton spent a few days testing Jacket to accelerate MATLAB on NVIDIA GPUs, and found it surprisingly easy to speed up DSP code. He ran 2D FFT and interp2 benchmarks on a MacBook Air with a GeForce 9400M, seeing impressive speedups for large images while hitting GPU memory and precision limits at high sizes. The post shares practical tips on casting to GPU types, minimizing CPU-GPU transfers, and when GPU acceleration is most useful.
OpenCV for DSP/GPU, MSDN equivalent for CCS, and more
Porting OpenCV to DSPs could be a real business opportunity, but it is far from trivial, writes Shehrzad Qureshi. He highlights major obstacles: the engineering scale, mixed open-source licenses, and hard-to-parallelize primitives like connected components. He also criticizes Code Composer Studio's help system compared with MSDN, notes an ATI Stream talk, and announces a CUDA walkthrough on FFT-based image filtering.
Music/Audio Signal Processing
Julius Orion Smith III traces his journey from musician to music/audio DSP researcher, sharing the choices that shaped his career and research focus. He recounts work on violin modeling and waveguide synthesis, then highlights modern prototyping tools like Faust and Octave that accelerate experimentation. Read for practical career advice on coursework, publishing, and why free open-source tools matter for rapid audio research.
Frequency Dependence in Free Space Propagation
Free-space propagation of electromagnetic waves is essentially independent of frequency, a counterintuitive conclusion Eric Jacobsen demonstrates step by step. He shows the λ^2 factor in the Friis transmission equation comes from antenna effective area and gain, not from the space between antennas, explaining why dipoles favor lower bands while dishes improve with frequency. The post also reminds engineers that material penetration and atmospheric absorption remain genuine frequency dependent concerns.
Understanding and Implementing the Sliding DFT
The Sliding DFT delivers exact DFT results with per-sample frequency updates, making real-time spectral processing far more efficient than repeatedly running an FFT. Eric Jacobsen walks through the derivation, presents the simple recursive update, and covers practical concerns such as initialization and fixed-point stability. Engineers building low-latency, low-power systems will appreciate the algorithm's computational and latency advantages.
Model a Sigma-Delta DAC Plus RC Filter
Sigma-delta digital-to-analog converters (SD DAC’s) are often used for discrete-time signals with sample rate much higher than their bandwidth. For the simplest case, the DAC output is a single bit, so the only interface hardware required is a standard digital output buffer. Because of the high sample rate relative to signal bandwidth, a very simple DAC reconstruction filter suffices, often just a one-pole RC lowpass. In this article, I present a simple Matlab function that models the combination of a basic SD DAC and one-pole RC filter. This model allows easy evaluation of the overall performance for a given input signal and choice of sample rate, R, and C.
ES Week Emphasis on Component Based Design
ES Week in Salzburg brought a strong theme into focus, component based design and automation for embedded and MPSoC systems. Praveen Raghavan highlights a few standout keynotes and industry talks, from SDR evolution at Infineon to Tensilica’s push toward instruction set extension and MPSoC assembly. He also notes Toshiba’s new VLIW vector processor for image and video front ends, along with the compiler challenges that come with it.
Setting the 3-dB Cutoff Frequency of an Exponential Averager
Many engineers use a simple exponential averager but need the correct α to achieve a specified 3-dB cutoff. Rick Lyons compares a common approximation with the exact closed-form solution, shows when the approximation is valid, and derives the exact α in the appendix. The approximation works well for fc < 0.1fs, but it becomes noticeably inaccurate as the normalized cutoff increases.
Sampling bandpass signals
Bandpass signals can be sampled at rates below the usual Nyquist limit, and this note shows how the band-limited spectrum appears in baseband after sampling. Using a simple example figure, it defines the center frequency fc = (fmax + fmin)/2 and bandwidth Δf = fmax - fmin, and highlights that choosing fs less than twice the signal's highest frequency violates the sampling theorem.
A poor man's Simulink
Markus Nentwig built a compact glue layer that embeds NGSPICE into Octave to cosimulate continuous-time circuits and digital control. The article walks through an RC lowpass example, the MEX-based Octave interface, and the breakpoint-driven cosimulation flow, showing how adaptive SPICE integration handles asynchronous and time-triggered events. It presents a practical, low-cost alternative to Simulink for tightly coupled analog-digital system design.
Recruiting New Bloggers!
EmbeddedRelated is expanding its blogging team, and Stephane Boucher is inviting engineers, students, hobbyists, and researchers to contribute. He points to the success of earlier contributors and says the community has already read their articles more than 1,250,000 times. If you have knowledge to share, this post explains how to pitch a topic and get started.
Wavelets II - Vanishing Moments and Spectral Factorization
This post walks through how vanishing moments turn into concrete algebraic constraints on wavelet filter coefficients, and why that leads to Daubechies filters. It explains how a wavelet with A vanishing moments is orthogonal to all polynomials up to degree A minus one, and it shows how those continuous conditions become discrete sums like sum_k k^n h1(k)=0. Expect clear links between approximation power and filter length.
Goertzel Algorithm for a Non-integer Frequency Index
Rick Lyons demonstrates how to run the Goertzel algorithm with a non-integer frequency index k, letting you target DTFT frequencies that do not align with DFT bin centers. He interprets Rajmic and Sysel's generalization, provides a simple implementation, and presents a real-valued reformulation that reduces the final multiplies for real inputs. Example Matlab code is included to reproduce and adapt the technique.
Signed serial-/parallel multiplication
Struggling with costly wide adders for signed multiplication on FPGAs? Markus Nentwig unpacks a neat bit-level trick that turns two's-complement signed-signed multiplication into a serial-parallel routine using only a one-bit wider adder. Learn how flipping sign bits and a small, controlled constant cancel lets you avoid full sign-extension, and get a parametrized Verilog RTL plus synthesis notes to try it yourself.
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.
Discrete-Time PLLs, Part 1: Basics
In this series of tutorials on discrete-time PLLs we will be focusing on Phase-Locked Loops that can be implemented in discrete-time signal proessors such as FPGAs, DSPs and of course, MATLAB.
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.
