The History of CIC Filters: The Untold Story
Hogenauer's 1981 paper is the canonical CIC reference, but this post uncovers an earlier, practical origin story: engineer Richard Newbold used and documented a CIC decimation filter in late 1979. Rick Lyons recounts how Newbold’s HP-35 calculations produced the now-familiar frequency-response plot that appeared in Hogenauer's paper, why managers feared a pole at DC, and how demonstrations won adoption.
scipy.signal calling all developers
SciPy’s signal-processing toolbox is at a crossroads, and Christopher Felton is urging developers to jump in. He points to active discussion on scipy-dev, the possibility of a separate scikit-signal effort, and the broad set of functions already in scipy.signal. If you work in DSP and like open-source software, this is a good moment to look at the package, and maybe help shape it.
Oscilloscope Dreams
Jason Sachs walks through practical oscilloscope buying criteria for embedded engineers, focusing on bandwidth, channel count, hi-res acquisition, and probing. He explains why mixed-signal scopes and hi-res mode matter, when a 100 MHz scope is sufficient and when to keep a higher-bandwidth instrument, and how probe grounding and waveform export can ruin measurements. Real-world brand notes and try-before-you-buy advice round out the guidance.
[Book Review] Numpy 1.5 Beginner's Guide
Christopher Felton's review gives a pragmatic take on Ivan Idris's Numpy 1.5 Beginner's Guide, praising its hands-on, exercise-driven approach while flagging several shortcomings. He finds the book a useful starting point for newcomers to Python numerical computing thanks to practical examples and a chapter on testing, but warns the title, incomplete installation guidance, and some factual errors may mislead readers.
Design study: 1:64 interpolating pulse shaping FIR
Markus Nentwig presents a practical 1:64 root-raised cosine interpolator built from cascaded FIR stages that slashes computational cost. By separating pulse shaping from rate conversion, designing each interpolator to suppress only known alias bands, and equalizing the pulse shape, the design achieves just 4.69 MACs per output, roughly 12 percent of a straight polyphase implementation while meeting EVM targets.
Accurate Measurement of a Sinusoid's Peak Amplitude Based on FFT Data
Measuring a sinewave's peak from FFT data can be severely biased by scalloping loss, producing errors up to 36.3 percent. Rick Lyons demonstrates how to apply a flat-top window via frequency-domain convolution to the FFT bins, cutting maximum amplitude error to about 0.02 dB compared with 3.9 dB for rectangular windows. The post includes Matlab code and practical caveats for reliable use.
Generating Complex Baseband and Analytic Bandpass Signals
Rick Lyons gathers and compares practical methods for creating complex baseband and analytic bandpass signals in one compact reference. The post clarifies definitions, lists time and frequency domain techniques from quadrature sampling to FFT-based analytic generation, and notes implementation tradeoffs such as sample-rate constraints, Hilbert transformer use, and phase linearity concerns. Engineers get a quick Hit Parade of options and pointers to deeper references.
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.
Python number crunching faster? Part I
Christopher Felton walks through simple benchmarks comparing raw Python, numpy, and PyPy for numeric workloads, and shares what surprised him about performance. He shows that idiomatic Python optimizations such as list comprehensions and built-ins plus the PyPy JIT can sometimes beat a numpy approach for small tests, and explains why native PyPy numpy progress matters for scientific users.
More free Ebooks
A handy roundup of free engineering ebooks and journals, with a focus on where DSPRelated readers might actually find useful material. The post points to InTechOpen, highlights several MATLAB books, and even calls out a numerical methods title plus some sensor fusion content. If you like browsing for practical references, this is a good place to start.
A Table of Digital Frequency Notation
Rick Lyons compiles a compact, practical table that untangles the many algebraic frequency notations used in DSP. The reference lines up continuous and discrete sinusoid forms, shows the frequency variable names and units, and lists valid ranges and conversions like Ω = 2πf and normalized forms with fs. A printable PDF of the table is available for easy desk reference.
New Comments System (please help me test it)
DSPRelated just got a practical upgrade, Stephane Boucher has released a new comments system built from his earlier forum work. It supports drag-and-drop or Insert Image uploads, MathML, TeX and ASCIImath rendered by MathJax, syntax-highlighted code via highlight.js, and in-place editing and deletion of comments. Improved email notifications alert authors and commenters to replies, and readers are invited to post test comments and report problems.
There's No End to It -- Matlab Code Plots Frequency Response above the Unit Circle
If you want a fresh way to inspect a digital filter, this post introduces plotfil3d, a compact MATLAB function that wraps the magnitude response around the unit circle in the Z-plane so you can view it in 3D. It uses freqz to compute H(z) in dB for N points and accepts an optional azimuth to change the viewing angle; the code is provided in the appendix.
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.
Ten Little Algorithms, Part 6: Green’s Theorem and Swept-Area Detection
Jason shows how Green's Theorem becomes a practical, low-cost method to detect real-time rotation from two orthogonal sensors by accumulating swept area. The post derives a compact discrete integrator S[n] = S[n-1] + (x[n]*(y[n]-y[n-1]) - y[n]*(x[n]-x[n-1]))/2, compares integer and floating implementations, and analyzes noise scaling and sampling rate tradeoffs. Includes Python demos and threshold guidance.
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.
Orfanidis Textbooks are Available Online
Two classic signal processing textbooks by Sophocles J. Orfanidis are now available for download from his Rutgers webpages. The first, Introduction to Signal Processing, includes errata and a homework solutions manual. The second, Optimum Signal Processing, includes a solutions manual plus MATLAB, C and Fortran code. Note that Prof. Orfanidis retains copyright on both books, All Rights Reserved.
A Useful Source of Signal Processing Information
A surprisingly handy web tool turned up for finding signal processing material in PDF and PowerPoint form. Rick Lyons shows how a plain-looking site can surface lots of topic-specific documents, using FM demodulation as the example. If you often hunt for reference slides and papers, this is a quick source worth bookmarking.
Linear Feedback Shift Registers for the Uninitiated, Part XII: Spread-Spectrum Fundamentals
Jason Sachs shows why LFSR-generated pseudonoise is a natural fit for direct-sequence spread spectrum, then walks through Fourier basics, spectral plots, and runnable Python examples. The article demonstrates how DSSS multiplies a UART bitstream with a chipping sequence to spread energy, how despreading concentrates the desired signal while scrambling narrowband interference, and how multiple transmitters can share bandwidth when using uncorrelated sequences.
Ancient History
Technology moves fast, and the tools, platforms, and assumptions you rely on can become outdated almost overnight. In this reflective post, the author contrasts the rapid evolution of embedded development with the much slower pace of social change, from programming turnaround times to the underrepresentation of women in engineering. It is a reminder to keep learning, but also to think about how we work and who gets included.
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.
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.
The 2024 DSP Online Conference
The DSP Online Conference returns for a fourth year, running October 29–31, with a program designed for students, engineers, hobbyists, and experts. Organized into four tracks—general DSP theory, communications, audio, and DSP with deep learning—the event accepts short MicroTalks through two-hour Workshops and offers early-bird registration plus immediate archive access for registrants.
DFT Bin Value Formulas for Pure Complex Tones
Cedron Dawg derives closed-form DFT bin formulas for single complex exponentials, eliminating the need for brute-force summation and showing how phase acts as a uniform rotation of all bins. He also gives a Dirichlet-kernel form that yields the magnitude as (M/N)|sin(δN/2)/sin(δ/2)|, explains the large-N sinc limit, and includes C code to verify the results.
Two Bin Exact Frequency Formulas for a Pure Real Tone in a DFT
Cedron Dawg derives exact, closed-form frequency formulas that recover a pure real tone from just two DFT bins using a geometric vector approach. The method projects bin-derived vectors onto a plane orthogonal to a constraint vector to eliminate amplitude and phase, yielding an explicit cos(alpha) estimator; a small adjustment improves noise performance so the estimator rivals and slightly betters earlier two-bin methods.
'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.
A Table of Digital Frequency Notation
Rick Lyons compiles a compact, practical table that untangles the many algebraic frequency notations used in DSP. The reference lines up continuous and discrete sinusoid forms, shows the frequency variable names and units, and lists valid ranges and conversions like Ω = 2πf and normalized forms with fs. A printable PDF of the table is available for easy desk reference.
TI DSP Predictions
Jeff Brower lays out two bold predictions for Texas Instruments that could reshape the DSP developer ecosystem. He argues TI will offer a supported real-time Linux on their C6x DSPs now that legal obstacles have eased, and that TI may acquire an FPGA company to own the board space around its chips. Read to weigh the technical and strategic impact.
A Recipe for a Basic Trigonometry Table
Cedron Dawg walks through building a degree-based sine and cosine table from first principles, showing both recursive and multiplicative complex-tone generators. The article highlights simple drift-correction tricks such as mitigated squaring and compact normalization, gives series methods to compute one-degree and half-degree values, and includes practical C code that ties the table to DFT usage and frequency estimation.
Constrained Integer Behavior
Overflow and underflow are not always bugs, they can be useful in DSP when fixed-width integers wrap during processing. Christopher Felton demonstrates with moving-average (recursive-windowed-averager) and CIC filter examples how 2's complement wraparound in MyHDL's modbv cancels between an integrator and a comb via pole-zero cancellation. He also covers fixed-point resizing choices, saturation versus wrap, and how rounding error can accumulate.
