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.
GPGPU DSP
Shehrzad Qureshi kicks off his DSP blog by championing GPGPU, focusing on Nvidia's CUDA and real-product experience. He argues that with CPU clock speeds stalled, large-scale parallelism on GPUs is the practical path forward for many signal-processing tasks. The post traces GPGPU history from shader 'hacks' to modern APIs and previews future posts comparing CUDA vs OpenCL, Intel's Larrabee, and Nvidia Fermi.
The Nature of Circles
Averaging angles the usual way can produce nonsense: the mean of 0 and 359 degrees is not 179.5 when working with circular data. Peter Kootsookos shows the correct approach using vectorial or phasor averaging, converting angles to unit complex numbers and taking the argument of their sum. The short post points to directional statistics and a related IEEE paper for deeper details.
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.
Time Machine, Anyone?
Causal filters can look like time machines, but they do not break physics. Andor Bariska reproduces a classic electronic experiment in MATLAB, showing how a minimum-phase peaking filter and its FDLS biquad approximation produce negative group delay bands that make predictable, bandlimited signals appear to emerge early. The post walks through group delay, discretization, pulse and random-signal tests, and why unpredictability restores causality.
Benford's law solved with DSP
Steve Smith shows that standard DSP tools give a clean, intuitive explanation of Benford's law by treating leading-digit counts as signals on the number line and using convolution and Fourier analysis. He publishes the full derivation as an online chapter after traditional journals showed little interest. The result highlights how time- and spatial-domain DSP techniques can be applied to numeric distributions.
Waveforms that are their own Fourier Transform
Steve Smith admits a long-standing mistake and overturns the claim that only Gaussians are their own Fourier transform. He gives trivial and nontrivial examples, explains why infinitely many such waveforms exist, and shows a quick discrete construction using the DFT with a 1/sqrt(N) normalization. Engineers get an intuitive 30-second argument plus a practical recipe to build self-Fourier signals.
Computing Chebyshev Window Sequences
Rick Lyons gives a compact, practical recipe for building M-sample Chebyshev (Dolph) windows with user-set sidelobe levels, not just theory. The post walks through computing α and A(m), evaluating the Nth-degree Chebyshev polynomial, doing an inverse DFT, and the simple postprocessing needed to form a symmetric time-domain window. A worked 9-sample example and an implementation caveat for even-length windows make this immediately usable.
An Interesting Fourier Transform - 1/f Noise
Power-law signals have a neat Fourier trick: their transforms are power laws too, but with important caveats. Steve Smith walks through the t^α ↔ ω^{-(α+1)} relation, shows how the unit step, the Gamma scaling and a nontrivial phase change the picture, and highlights the special α = -0.5 case that links to 1/f noise. The post frames why phase and physical interpretation keep 1/f noise mysterious.
Components in Audio recognition - Part 1
This post introduces the core components of an audio recognition system, framed against how the human auditory system naturally familiarizes and retrieves tunes. Prabindh Sundareson outlines the three building blocks: an archive store, an analysis and fingerprinting engine that groups tracks, and a front-end that accepts queries and places samples into groups. He previews upcoming posts that will dig into implementations and tradeoffs.
Software Defined Radio at SAMOS
At SAMOS, the SDR track drew a strong academic crowd, with groups from UMich, Wisconsin-Madison, Linköping, IMEC, and others presenting their latest ideas. Praveen Raghavan also notes that IMEC finally made its SyncPro architecture public, a vector synchronization processor design. The post gives a quick snapshot of where software defined radio research was active, and which major industry names were noticeably absent.
Overview of my Articles
Cedron presents a guided tour of his DSPRelated articles that teach the discrete Fourier transform through derivations, numerical examples, and sample code. The collection centers on novel "bin value" formulas and exact frequency estimators for complex and real tones, with methods for phase and amplitude recovery and iterative multitone resolution. The overview also points to a zeroing-sine window family and an integer pseudo-differentiator for efficient peak and zero-crossing detection.
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.
Computing Chebyshev Window Sequences
Rick Lyons gives a compact, practical recipe for building M-sample Chebyshev (Dolph) windows with user-set sidelobe levels, not just theory. The post walks through computing α and A(m), evaluating the Nth-degree Chebyshev polynomial, doing an inverse DFT, and the simple postprocessing needed to form a symmetric time-domain window. A worked 9-sample example and an implementation caveat for even-length windows make this immediately usable.
The Zeroing Sine Family of Window Functions
A previously unrecognized family of DFT window functions is introduced, built from products of shifted sines that deliberately zero out tail samples and control nonzero support. Cedron Dawg presents recursive and semi-root constructions, runnable code, and numerical examples, and shows that the odd-N member L=(N-1)/2 numerically matches a discrete Hermite-Gaussian DFT eigenvector. The post highlights practical properties, an even-N fix, and applications to spectrograms and tone decomposition.
Multimedia Processing with FFMPEG
FFMPEG is a set of libraries and a command line tool for encoding and decoding audio and video in many different formats. It is a free software project for manipulating/processing multimedia data. Many open source media players are based on FFMPEG libraries.
The Nature of Circles
Averaging angles the usual way can produce nonsense: the mean of 0 and 359 degrees is not 179.5 when working with circular data. Peter Kootsookos shows the correct approach using vectorial or phasor averaging, converting angles to unit complex numbers and taking the argument of their sum. The short post points to directional statistics and a related IEEE paper for deeper details.
The correct answer to the quiz of @apolin
A compact Simulink model explains why certain DFT rows behave like negative-frequency bandpass filters, using dftmtx(8) rows as impulse responses. The demo shows that a 2 kHz tone with phase 0 or pi produces identical real parts and opposite imaginary parts, making a negative-frequency interpretation unnecessary. It also illustrates how a 6 kHz tone under 8 kHz sampling aliases to 2 kHz with opposite phase, visible in PSD plots.
FREE Peer-reviewed IEEE signal processing courses
IEEE Signal Processing Society is offering a small set of free, peer-reviewed courses covering topics like wavelets, speech analysis, and statistical detection. The post points to these endorsed materials as a useful way to browse vetted DSP learning resources without paying for formal coursework.
Frequency Formula for a Pure Complex Tone in a DTFT
The analytic formula for calculating the frequency of a pure complex tone from the bin values of a rectangularly windowed Discrete Time Fourier Transform (DTFT) is derived. Unlike the corresponding Discrete Fourier Transform (DFT) case, there is no extra degree of freedom and only one solution is possible.
Compressive Sensing - Recovery of Sparse Signals (Part 1)
The amount of data that is generated has been increasing at a substantial rate since the beginning of the digital revolution. The constraints on the sampling and reconstruction of digital signals are derived from the well-known Nyquist-Shannon sampling theorem...
Why is Fourier transform broken
Many engineers know the Gibbs phenomenon without grasping its root cause. This post shows that the problem comes from using the incomplete metric space of continuous functions, C[a,b], for Fourier series, and explains how switching to Lp spaces resolves convergence in the mean but allows functions to differ on sets of measure zero. It also reminds readers that Fourier analysis gives no time localization, so be mindful of its limits.
Engineering the Statistics
Statistical analysis can get messy fast when theory and MATLAB simulations refuse to agree. This post shares a graduate student’s hard-earned shortcuts for taming random variables, from deriving a CDF or moments to using Gaussian or Gamma approximations, and falling back on Chernoff bounds when the exact PDF stays out of reach.
The Nature of Circles
Averaging angles the usual way can produce nonsense: the mean of 0 and 359 degrees is not 179.5 when working with circular data. Peter Kootsookos shows the correct approach using vectorial or phasor averaging, converting angles to unit complex numbers and taking the argument of their sum. The short post points to directional statistics and a related IEEE paper for deeper details.
State Space Representation and the State of Engineering Thinking
State space is common in control, but it shows up much less often in signal processing. This post argues that the difference is really about engineering priorities: for many DSP problems, transfer functions are enough, while state space becomes valuable when internal behavior matters, like filter scaling or Kalman filtering. It is a short, practical look at why engineers choose one model over the other.
GPGPU DSP
Shehrzad Qureshi kicks off his DSP blog by championing GPGPU, focusing on Nvidia's CUDA and real-product experience. He argues that with CPU clock speeds stalled, large-scale parallelism on GPUs is the practical path forward for many signal-processing tasks. The post traces GPGPU history from shader 'hacks' to modern APIs and previews future posts comparing CUDA vs OpenCL, Intel's Larrabee, and Nvidia Fermi.
ICASSP 2011 conference lectures online (for free)
For the first time, the oral sessions of ICASSP 2011 were recorded and posted online for free, giving engineers worldwide easy access to the conference. The talks span speech and communication signal processing, plus eclectic topics like bio-inspired methods, where Prof. Sayed uses a distributed LMS model to reproduce group predator and prey behavior. Expect some theoretical material, but many presentations are practical and inspiring for DSP practitioners.
FREE Peer-reviewed IEEE signal processing courses
IEEE Signal Processing Society is offering a small set of free, peer-reviewed courses covering topics like wavelets, speech analysis, and statistical detection. The post points to these endorsed materials as a useful way to browse vetted DSP learning resources without paying for formal coursework.
Components in Audio recognition - Part 1
This post introduces the core components of an audio recognition system, framed against how the human auditory system naturally familiarizes and retrieves tunes. Prabindh Sundareson outlines the three building blocks: an archive store, an analysis and fingerprinting engine that groups tracks, and a front-end that accepts queries and places samples into groups. He previews upcoming posts that will dig into implementations and tradeoffs.
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.
