Noise shaping
Markus Nentwig presents a compact, practical introduction to noise shaping by treating quantization error as the first sample of a designed impulse response. He shows how to derive a noise shaper from a target spectrum, demonstrates the tradeoff between in-band noise reduction and total noise increase, and includes a Matlab example while highlighting clipping and stability caveats for sigma-delta contexts.
Two jobs
Stephane Boucher explains why EmbeddedRelated went quiet for a few months after a volunteer project demanded more of his time. He and his wife organized a clown-gymnastics show with 15 kids, sold more than 700 of 800 tickets, and raised $2,700 for the Tree of Hope. Now the shows are done and he plans to resume regular posting with new site features.
Coupled-Form 2nd-Order IIR Resonators: A Contradiction Resolved
Rick Lyons resolves a long-standing confusion about the coupled-form 2nd-order IIR resonator by deriving its correct z-domain transfer function and explaining why textbooks can appear to contradict pole plots. He shows that with infinite precision the coupled and standard denominators match, but finite-bit quantization of rcos(Θ) and rsin(Θ) changes the z^-2 coefficient and shifts pole positions. Read to learn the correct H(z) to predict quantized behavior and when the coupled form outperforms the standard design.
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.
'z' as in 'Zorro': Frequency Masking FIR
Markus Nentwig shows an efficient way to build steep wideband FIR filters by combining upsampled and complementary stages, then masking their spectra. He provides a Matlab and Octave design program that uses a generic least-squares optimizer to place coefficients, letting you explore filter sizes and oversampling while cutting computational cost significantly compared to a conventional symmetric FIR.
Do you like the new Comments System?
Stephane Boucher has just rolled out a new comments system for the DSPRelated blogs and wants feedback from readers. He’s asking the community to try it out, share thoughts, and help shake out any issues before it gets expanded to the code snippets and papers sections.
FIR sideways (interpolator polyphase decomposition)
Markus Nentwig presents a compact way to implement a symmetric FIR interpolator by rethinking the usual tapped delay line. The 1:3 polyphase example uses separate delay lines per coefficient to skip multiplies on known zeros and exploit symmetry, cutting multiplications substantially; a Matlab/Octave demo and notes on ASIC-friendly implementation are included to help evaluate real-world cost tradeoffs.
Design of an anti-aliasing filter for a DAC
If you need a practical way to design an anti-aliasing filter for a DAC, this post delivers an Octave/Matlab script that numerically optimizes a Laplace-domain transfer function for linear phase and arbitrary magnitude. The routine models the DAC sample-and-hold sinc response, compensates group delay automatically, and can include an optional multiplierless FIR equalizer. An example shows a 5.4 dB objective improvement and reduced analog Q for easier implementation.
Understanding the 'Phasing Method' of Single Sideband Demodulation
Rick Lyons explains how the phasing method separates overlapping single sideband transmissions using quadrature processing and the Hilbert transform, making SSB demodulation practical in crowded RF environments. After reviewing simple synchronous detection, he walks through spectra and block diagrams that show how complex downconversion produces i and q paths which reinforce the desired sideband and cancel the other. The post also covers DSP implementation tips and BFO error effects.
Frequency-Domain Periodicity and the Discrete Fourier Transform
Sampling turns a continuous spectrum into an infinite set of replicas, and this article explains why the DFT and DTFT inevitably show periodic, circular spectra. Eric Jacobsen combines rigorous math with a geometric, wagon-wheel intuition to clarify aliasing, bandlimited sampling, and sampled-IF techniques. Read it to see when center frequency doesn't matter, how cyclic baseband shifts behave, and why bandwidth, not absolute frequency, determines alias-free sampling.
Polar Coding Notes: Channel Combining and Channel Splitting
Lyons Zhang walks through the core algebra of polar coding, showing how channel combining builds the vector channel W_N from N copies of a binary-input DMC using the polar transform G_N = B_N F^{⊗n}. The notes then define channel splitting, derive the coordinate-channel transition probabilities from the chain rule, and present the recursive formulas that let you compute W_{2N}^{(2i-1)} and W_{2N}^{(2i)} from W_N^{(i)}.
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.
Add a Power Marker to a Power Spectral Density (PSD) Plot
Read absolute power directly from a PSD plot with a simple MATLAB helper. The author presents psd_mkr, a function that computes the PSD with pwelch and overlays a power marker in three modes: normal for narrowband tones, band-power for integrated power over a specified bandwidth, and 1 Hz for noise density readings. Examples show how bin summing, window loss, and scalloping are handled for accurate measurements.
Radio Frequency Distortion Part II: A power spectrum model
Markus Nentwig presents a power-spectrum model that predicts RF nonlinear distortion from spectral power values instead of time-domain signals. The model computes distortion as repeated convolutions with a frequency-reversed replica and uses an FFT/IFFT trick with real-valued arithmetic for very high efficiency, making it suitable for system-level simulations and interference-aware radios. It is accurate for OFDM-like, Gaussian-amplitude signals when spectral binning is sufficiently fine; narrowband cases require denser bins.
Implementing Impractical Digital Filters
Some published IIR block diagrams are impossible to implement because they contain delay-less feedback paths, and Rick Lyons shows how simple algebra fixes that. He works through two concrete examples—a bandpass built from a FIR notch and a narrowband notch using a feedback loop—and derives equivalent, implementable second-order IIR transfer functions. The post emphasizes spotting problematic loops and replacing them with practical block diagrams.
New Code Sharing Section & Reward Program for Contributors!
DSPRelated is launching a new code sharing section and looking for contributors to help seed it with useful DSP snippets. Stephane Boucher also introduces a pageview-based reward program, with payouts tied to unique visits so popular code can earn contributors up to $250. It is a practical push to build a high-quality library for the DSP community from the start.
Curse you, iPython Notebook!
Christopher Felton shares a cautionary tale about losing an ipython 0.12 notebook session after assuming the browser would save his interactive edits. He explains that notebooks at the time required clicking the top Save button to persist sessions, and autosave was not yet available. He recommends basing interactive work on scripts, saving often, and testing export behavior to avoid redoing text, LaTeX, and plots.
Implementing Simultaneous Digital Differentiation, Hilbert Transformation, and Half-Band Filtering
Recently I've been thinking about digital differentiator and Hilbert transformer implementations and I've developed a processing scheme that may be of interest to the readers here on dsprelated.com.
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.
Filter a Rectangular Pulse with no Ringing
You can filter a rectangular pulse with no ringing simply by using an FIR whose coefficients are all positive, and make them symmetric to get identical leading and trailing edges. This post walks through a MATLAB example that convolves a normalized Hanning window with a 32-sample rectangular pulse, showing that window length controls edge duration and that shorter windows widen the spectrum. It also notes this is not a QAM pulse-shaping solution.
A Remarkable Bit of DFT Trivia
Rick Lyons highlights a surprising equality: the DFT's worst-case scalloping loss equals 2/π, the same probability that a toothpick crosses a floorboard seam in Buffon's needle problem when the toothpick equals board width. The post sketches the DFT bin-intersection derivation and connects the math to the classic probability puzzle, offering a playful insight that sharpens intuition about bin responses.
A Lesson in Statistics Using Random Sequences
Statistics may come naturally to some people, but it is a difficult subject for many of us. Using simulations helps to remove some of the mystery of statistics. Luckily, it is trivial to produce a pseudo-random Gaussian or uniform sequence: a single command in Matlab (or Python) does it. In this article, I try to explain a few concepts using Gaussian and uniform random sequences generated in Matlab. First, we’ll generate a Gaussian sequence, calculate its variance, and plot a histogram and probability density function (PDF). Next, we’ll simulate the roll of a single die to illustrate a uniform distribution. Then we’ll simulate rolling two dice and finally, as an illustration of the Central Limit Theorem, we’ll sum the total when rolling several dice to obtain an approximately Gaussian distribution.
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.
Filter a Rectangular Pulse with no Ringing
You can filter a rectangular pulse with no ringing simply by using an FIR whose coefficients are all positive, and make them symmetric to get identical leading and trailing edges. This post walks through a MATLAB example that convolves a normalized Hanning window with a 32-sample rectangular pulse, showing that window length controls edge duration and that shorter windows widen the spectrum. It also notes this is not a QAM pulse-shaping solution.
A Direct Digital Synthesizer with Arbitrary Modulus
Need exact sampled tones on a coarse grid without a huge sine table? This post shows how to build a Direct Digital Synthesizer with an arbitrary modulus so the output frequency is exactly k·fs/L, using a look-up table as small as 20 entries for the 10 MHz/0.5 MHz-step example. It also explains fixed-point LUT rounding, accumulator bit sizing, and how to produce quadrature outputs when L is multiple of 4.
Phase and Amplitude Calculation for a Pure Complex Tone in a DFT
Cedron Dawg derives compact, exact formulas to recover the phase and amplitude of a single complex tone from a DFT bin when the tone frequency is known. The paper turns the complex bin value into closed-form expressions using a sine-fraction amplitude correction and a simple phase shift, and includes working code plus a numeric example for direct implementation.
The Discrete Fourier Transform of Symmetric Sequences
Symmetric sequences arise often in digital signal processing. Examples include symmetric pulses, window functions, and the coefficients of most finite-impulse response (FIR) filters, not to mention the cosine function. Examining symmetric sequences can give us some insights into the Discrete Fourier Transform (DFT). An even-symmetric sequence is centered at n = 0 and xeven(n) = xeven(-n). The DFT of xeven(n) is real. Most often, signals we encounter start at n = 0, so they are not strictly speaking even-symmetric. We’ll look at the relationship between the DFT’s of such sequences and those of true even-symmetric sequences.
Simple Discrete-Time Modeling of Lossy LC Filters
Converting a lossy LC filter into a discrete-time impulse response lets you analyze mixed analog and DSP systems in one time domain. This post walks through computing the LC frequency response via chain (ABCD) parameters including resistive losses, enforcing the Hermitian symmetry required for a real IDFT, and using the IDFT to produce an asymmetrical FIR impulse response. A 5th-order Butterworth example illustrates insertion loss and impulse-shape effects.
Polar Coding Notes: Channel Combining and Channel Splitting
Lyons Zhang walks through the core algebra of polar coding, showing how channel combining builds the vector channel W_N from N copies of a binary-input DMC using the polar transform G_N = B_N F^{⊗n}. The notes then define channel splitting, derive the coordinate-channel transition probabilities from the chain rule, and present the recursive formulas that let you compute W_{2N}^{(2i-1)} and W_{2N}^{(2i)} from W_N^{(i)}.
Add a Power Marker to a Power Spectral Density (PSD) Plot
Read absolute power directly from a PSD plot with a simple MATLAB helper. The author presents psd_mkr, a function that computes the PSD with pwelch and overlays a power marker in three modes: normal for narrowband tones, band-power for integrated power over a specified bandwidth, and 1 Hz for noise density readings. Examples show how bin summing, window loss, and scalloping are handled for accurate measurements.
