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.
Python scipy.signal IIR Filter Design Cont.
Christopher Felton continues his practical tour of SciPy's iirdesign, moving beyond lowpass examples to show highpass, bandpass, and stopband designs with concise, code-focused explanations. He highlights how ellip and cheby2 let you tighten specifications for sharper transitions, and shows that the iirdesign workflow is consistent across filter types. Read for clear, reusable examples to produce IIR filter coefficients with scipy.signal.
Python scipy.signal IIR Filter Design
Christopher Felton walks through designing infinite impulse response filters using scipy.signal in Python, focusing on practical specs and functions rather than theoretical derivations. He explains normalized passband and stopband definitions, gpass and gstop, and shows how iirdesign and iirfilter differ. Plots compare elliptic, Chebyshev, Butterworth and Bessel responses, highlighting steep transitions versus near-linear phase tradeoffs.
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.
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.
[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.
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.
Resolving 'Can't initialize target CPU' on TI C6000 DSPs - Part 2
Mike Dunn walks through practical, low-level debugging to fix "Can't initialize target CPU" on TI C6000 DSPs using CCS 3.3, focusing on XDS510-class emulators. He demonstrates how to run xdsprobe to perform JTAG resets, read and interpret adapter and port error messages, and run JTAG IR/DR integrity tests. The article shows example outputs and a simple scope-based trace to locate signal faults.
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.
Discrete Wavelet Transform Filter Bank Implementation (part 1)
David Valencia walks through a practical implementation of discrete wavelet transform filter banks, focusing on cascading branches and efficient equivalent filters. He contrasts DWT and DFT resolution behavior and shows how cascading the low-pass branch sharpens frequency division while the high-pass path remains unchanged. Code pointers and a preview of formfilters() demonstrate how to compute only the needed samples by combining filters with upsampling.
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.
Is It True That j is Equal to the Square Root of -1 ?
A viral YouTube video claimed that saying j equals the square root of negative one is wrong. Rick Lyons shows the apparent paradox comes from misusing square-root identities with negative arguments, not from the usual definition of j. He argues it is safer to define j by j^2 = -1 and illustrates how careless root operations produce contradictions in two appendices.
Resolving 'Can't initialize target CPU' on TI C6000 DSPs - Part 1
Misconfigured Code Composer Studio settings cause most 'Can't initialize target CPU' errors on TI C6000 boards, not a faulty silicon. Mike Dunn walks through the practical first steps: confirm your CCS version, identify the exact emulator and board or device part number, and ensure you have the correct emulator driver. The post also shows how to duplicate TI's factory board configuration to avoid common setup mistakes.
Discrete Wavelet Transform Filter Bank Implementation (part 2)
David Valencia walks through practical differences between the discrete wavelet transform and the discrete wavelet packet transform, showing why DWPT yields symmetric frequency resolution while DWT favors a single high-pass branch. He explains how Noble identities let you collapse multi-branch filter banks into equivalent single convolutions, then compares block convolution matrices with chain-processing and links to MATLAB code for both approaches.
Digging into an Audio Signal and the DSP Process Pipeline
In this post, I'll look at the benefits of using multiple perspectives when handling signals.A Pre-existing Audio File
Let's say we have an audio file of interest. Let's load it into Audacity and zoom in a little (using View → Zoom → Zoom In, multiple times). The figure illustrates the audio signal: just a basic single-tone signal.
By continuing to zoom into the signal, we eventually get to the point of seeing individual samples as illustrated below. Notice that I've marked one...
Of Forests and Trees and DSP
Too often DSP engineers fixate on algorithms and miss the rest of the product. Tim Wescott uses the humble Korg CA-20 chromatic tuner to show that a great algorithm alone does not make a usable device, you also need good data acquisition, adequate processing, sensible precision, a usable UI, and appropriate casing and cost. The post gives practical do's and don'ts for system-level DSP design.
Analytic Signal
In communication theory and modulation theory we always deal with two phases: In-phase (I) and Quadrature-phase (Q). The question that I will discuss in this blog is that why we use two phases and not more.
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.
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.
A Two Bin Exact Frequency Formula for a Pure Complex Tone in a DFT
Cedron Dawg derives an exact two-bin frequency formula for a pure complex tone in the DFT, eliminating amplitude and phase to isolate frequency via a complex quotient and the complex logarithm. He presents an adjacent-bin simplification that replaces a complex multiply with a bin offset plus an atan2 angle, and discusses integer-frequency handling and aliasing. C source and numerical examples show the formula working in practice.
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.
Phase and Amplitude Calculation for a Pure Complex Tone in a DFT using Multiple Bins
Cedron presents exact, closed-form formulas to extract the phase and amplitude of a pure complex tone from multiple DFT bin values, using a compact vector formulation. The derivation introduces a delta variable to simplify the sinusoidal bin expression, stacks neighboring bins into a basis vector, and solves for the complex amplitude q by projection. The phase and magnitude follow directly from q, and extra bins reduce leakage when the tone falls between bins.
Approximating the area of a chirp by fitting a polynomial
Once in a while we need to estimate the area of a dataset in which we are interested. This area could give us, for example, force (mass vs acceleration) or electric power (electric current vs charge).
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.
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.
Determination of the transfer function of passive networks with MATLAB Functions
Starting the calculation from the output makes deriving a passive network transfer function simple, and this post shows how to do it in MATLAB using a sixth-order low-pass example. The walkthrough uses tf('s') to build a symbolic H(s), extracts coefficients with tfdata, and shows numerical frequency-response plotting via freqs or direct j*omega evaluation, with code and component values to reproduce the results.
Candan's Tweaks of Jacobsen's Frequency Approximation
Cedron Dawg shows how small tweaks to Jacobsen's three-bin frequency estimator turn a popular approximation into an exact formula, and how a modest cubic correction yields a near-exact, low-cost alternative. The article derives an arctan/tan exact recovery, relates it to Candan's 2011/2013 tweaks, and supplies reference C code and numerical tables so engineers can see when each formula is sufficient.
