Bayes meets Fourier
Bayes filters and Fourier transforms turn out to have a neat symmetry: prediction uses convolution, while measurement update uses multiplication. In this post, Allen Downey shows how the characteristic function ties Bayes filtering to the Fourier domain, then uses that connection to sketch an FFT-based implementation that can speed up the predict-update cycle. If you like Bayesian estimation and signal processing, this is a satisfying crossover.
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.
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.
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.
The Most Interesting FIR Filter Equation in the World: Why FIR Filters Can Be Linear Phase
Rick Lyons pulls back the curtain on a little-known coefficient constraint that makes complex-coefficient FIR filters exhibit linear phase. Rather than simple symmetry of real coefficients, the key is a conjugate-reflection relation involving the filter phase at DC, which collapses to ordinary symmetry for real taps. The post includes derivations, intuition using the inverse DTFT, and a Matlab example to verify the result.
Four Ways to Compute an Inverse FFT Using the Forward FFT Algorithm
Rick Lyons lays out four practical techniques to get an inverse FFT when you only have forward FFT software or FPGA cores available. The post highlights a classic data-reversal trick, a conjugate-symmetry optimized flow, and two methods that avoid reversals using data swapping or complex conjugation plus scaling. Each method notes when it is preferable so engineers can pick the least costly implementation.
Correcting an Important Goertzel Filter Misconception
A common claim says the Goertzel algorithm is marginally stable and prone to numerical errors. Rick Lyons shows that the usual second-order Goertzel filter has conjugate poles exactly on the unit circle, so pole placement alone does not make it unstable. The practical limits are coefficient quantization, which reduces frequency precision, and accumulator overflow for very large N.
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.
Premium Forum?
Stephane Boucher proposes a paid "premium" forum for DSPRelated that would redistribute membership fees to the community s top contributors via voting. The plan frames the $20/year fee as an incentive mechanism, not a revenue stream, with monthly payouts to the most appreciated posters. Boucher invites reader feedback to decide whether to implement the idea or pursue alternatives.
Phase and Amplitude Calculation for a Pure Real Tone in a DFT: Method 1
Cedron Dawg shows how to get exact amplitude and phase for a real sinusoid whose frequency does not land on an integer DFT bin. The method treats a small neighborhood of DFT bins as a complex vector, builds two basis vectors from the cosine and sine transforms, and solves a 2x2 system using conjugate dot products to recover real coefficients that give amplitude and phase. A C++ example and sample output verify the formulas.
Update to a Narrow Bandpass Filter in Octave or Matlab
Paul Lovell presents an updated, compact Octave/Matlab implementation of a narrow bandpass FIR that runs about four times faster and uses float32 to cut processing cost. The design combines a single matrix IFIR stage with three moving-sum (RRS) stages per baseband, auto-calculates the IFIR expansion factor, and adds easier parameter setup plus WAV I/O and FFT plots. A TensorFlow Colab demo is also provided.
A Two Bin Solution
Cedron Dawg shows how a real sinusoid's frequency, amplitude and phase can be recovered from only two adjacent DFT bins. The article derives exact two-bin formulas, gives a clear Gambas reference implementation, and demonstrates that accurate parameters can be obtained with very few samples when the tone lies between the bins. It also explains when the method breaks down and how the real-valued unfurling improves robustness.
Three Bin Exact Frequency Formulas for a Pure Complex Tone in a DFT
Cedron Dawg derives closed-form three-bin frequency estimators for a pure complex tone in a DFT using a linear algebra view that treats three adjacent bins as a vector. He shows any vector K orthogonal to [1 1 1] yields a = (K·Z)/(K·D·Z) and derives practical K choices including a Von Hann (Pascal) kernel and a data-driven projection. The post compares estimators under noise and gives simple selection rules.
The Phase Vocoder Transform
Treating the phase vocoder as a continuous transform, this post frames PV(x,α,β) as a bijection on signal space and derives the domain constraints needed for an inverse mapping. It uses geometric intuition and group-theory analogies to explain negative and zero scalings, then brings the idea back to DSP to show how aliasing and phase artifacts appear. The Laroche and Dolson consistency measure D_M plus MATLAB experiments are used to compare classic and identity phase-locking reconstructions.
An Astounding Digital Filter Design Application
Rick Lyons was astonished by the ASN Filter Designer, a hands-on filter design tool that makes tweaking frequency responses as simple as dragging markers with your mouse. The software updates magnitude plots, z-plane pole/zero locations, and filter coefficients in real time, and it also includes a signal analyzer plus a MATLAB-like scripting language for custom coefficient generation. The post links to a demo and user guides so you can try it yourself.
Free DSP Books on the Internet - Part Deux
Rick Lyons updates his curated list of freely downloadable DSP textbooks, adding titles across communications, implementation, spectral analysis, audio restoration, mathematics and music theory. The post highlights readable introductions like Prandoni and Vetterli's Signal Processing for Communications and Vetterli and Kovacevic's Wavelets and Subband Coding, while reminding readers that these copyrighted books are free only for individual download and not for redistribution.
Why Time-Domain Zero Stuffing Produces Multiple Frequency-Domain Spectral Images
Zero stuffing in the time domain creates spectral copies, and Rick Lyons walks through why that happens using DFT and DFS viewpoints. He shows that inserting L-1 zeros between samples yields a longer DFT with replicated spectral blocks, and that true interpolation requires lowpass filtering to remove those images. The post uses a concrete L=3 example and an inverse-DFT summation proof to make the effect intuitive.
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.
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.
A Narrow Bandpass Filter in Octave or Matlab
Building very narrow FIR bandpass filters at high sample rates often yields extremely long impulse responses. This post shows a practical Octave/Matlab implementation that uses complex downconversion to baseband plus a multistage Matrix IFIR and running-sum cascade to slash computation. With the provided example (48 kHz, 850 Hz center, 10 Hz passband) you get <1 dB ripple and >60 dB stopband while running 20x to 100x faster than a single-stage FIR.
Instant CIC
Modeling CIC decimators in floating point is simpler than you might think, Markus Nentwig shows, if you treat the filter as a finite FIR by sampling its impulse response. The post compares a naive float time-domain implementation, an FFT-based frequency-domain approach, and the recommended method of computing the impulse response and using an off-the-shelf FIR filter, with code and plots.
Learn About Transmission Lines Using a Discrete-Time Model
A simple discrete-time approach makes lossless transmission-line behavior easy to simulate and visualize. The post introduces MATLAB functions tline and wave_movie to model uniform lossless lines with resistive terminations, compute time and frequency responses, and animate travelling waves. A microstrip pulse example shows how reflections produce ringing and how source matching nearly eliminates it, making this a practical learning tool.
FIR Filter to Match Any Magnitude and Phase Response
This post details a technique for designing high quality FIR filters that match arbitrary magnitude and phase responses.
Deconvolution by least squares (Using the power of linear algebra in signal processing).
When we deal with our normal discrete signal processing operations, like FIR/IIR filtering, convolution, filter design, etc. we normally think of the signals as a constant stream of numbers that we put in a sequence
Collaborative Writing Experiment: Your Favorite DSP Websites
Stephane Boucher invites the DSPRelated community to a live Google Docs experiment to crowdsource the best DSP websites. After a successful run with EmbeddedRelated, he opens a shared document where members can add, edit, and curate links in real time. The post explains the simple rules, notes revision rollback protection, and asks readers to refresh and help keep the list useful and spam-free while watching it evolve.
Bank-switched Farrow resampler
Markus Nentwig proposes a bank-switched variant of the Farrow resampler that breaks each impulse-response segment into multiple sub-segments, enabling accurate interpolation with lower-order polynomials and fewer multiplications per output. This trades increased total coefficient storage for computational savings. The post explains the concept, connects it to polyphase FIR interpolation, and provides Matlab/Octave and C example code for practical evaluation.
A New Contender in the Quadrature Oscillator Race
Rick Lyons highlights a compact quadrature oscillator introduced by A. David Levine and Martin Vicanek, offering guaranteed stability, accurate low-frequency tuning, and modest computational cost. The post walks through the simple u, v, w recurrences used for software implementation. Appendices provide transfer functions and an algebraic stability proof for engineers who want formal verification before deployment.
Interpolator Design: Get the Stopbands Right
In this article, I present a simple approach for designing interpolators that takes the guesswork out of determining the stopbands.
Reducing IIR Filter Computational Workload
Rick Lyons demonstrates a simple, practical way to cut the multiply count for IIR lowpass and highpass filters by converting them into dual-path allpass structures. The conversion preserves the original magnitude response while drastically reducing multiplies per input sample, for example turning a 5th-order IIR that needs 11 multiplies into an equivalent allpass form needing only five. The linked PDF includes theory, implementation notes, a design example, and MATLAB 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.
