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Tutorials

Discrete-Time PLLs, Part 1: Basics

Reza AmeliReza Ameli December 1, 20159 comments

In this series of tutorials on discrete-time PLLs we will be focusing on Phase-Locked Loops that can be implemented in discrete-time signal proessors such as FPGAs, DSPs and of course, MATLAB.


Multilayer Perceptrons and Event Classification with data from CODEC using Scilab and Weka

David NorwoodDavid Norwood November 25, 2015

For my first blog, I thought I would introduce the reader to Scilab [1] and Weka [2]. In order to illustrate how they work, I will put together a script in Scilab that will sample using the microphone and CODEC on your PC and save the waveform as a CSV file.


Multimedia Processing with FFMPEG

Karthick Kumaran A S VKarthick Kumaran A S V November 16, 2015

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.


Approximating the area of a chirp by fitting a polynomial

Alexandre de SiqueiraAlexandre de Siqueira November 15, 20158 comments

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).


GPS - some terminology!

Vivek SankaravadivelVivek Sankaravadivel October 30, 20153 comments

GPS looks simple on the surface, but Vivek's post breaks out the core terminology behind how a receiver actually locks on and figures out where it is. Using a bar-room analogy, he maps acquisition, tracking, ephemeris, and almanac to the steps a GPS receiver follows before solving for position from satellite signals.


The Most Interesting FIR Filter Equation in the World: Why FIR Filters Can Be Linear Phase

Rick LyonsRick Lyons August 18, 201517 comments

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.


Phase and Amplitude Calculation for a Pure Real Tone in a DFT: Method 1

Cedron DawgCedron Dawg May 21, 20151 comment

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.


Exact Frequency Formula for a Pure Real Tone in a DFT

Cedron DawgCedron Dawg April 20, 20152 comments

Cedron Dawg derives an exact closed form formula to recover the frequency of a pure real sinusoid from three DFT bins, challenging the usual teaching that it is impossible. The derivation solves for cos(alpha) in a bilinear form and gives a computationally efficient implementation (eq.19), with practical notes on implicit Hann-like weighting and choosing the peak bin for robustness.


DFT Bin Value Formulas for Pure Real Tones

Cedron DawgCedron Dawg April 17, 20151 comment

Cedron Dawg derives a closed-form expression for the DFT bin values produced by a pure real sinusoid, then uses that formula to explain well known DFT behaviors. The post walks through the algebra from Euler identities to a compact computational form, highlights the integer versus non-integer frequency cases, and verifies the result with C code and printed numeric output.


DFT Graphical Interpretation: Centroids of Weighted Roots of Unity

Cedron DawgCedron Dawg April 10, 20151 comment

DFT bin values can be seen as centroids of weighted roots of unity, a geometric picture that makes many DFT properties immediate. Cedron Dawg uses the geometric-series identity and polar plots of integer and fractional tones to show why constants appear only at DC, how wrapping relates to bin index, and how phase, scaling, offsets, and real-signal symmetry affect bin magnitudes and angles.


DFT Bin Value Formulas for Pure Complex Tones

Cedron DawgCedron Dawg March 17, 2017

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.


A Recipe for a Basic Trigonometry Table

Cedron DawgCedron Dawg October 4, 2022

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.


Frequency Formula for a Pure Complex Tone in a DTFT

Cedron DawgCedron Dawg November 12, 2023

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.


Exact Near Instantaneous Frequency Formulas Best at Peaks (Part 2)

Cedron DawgCedron Dawg June 11, 20174 comments

Cedron Dawg derives a second family of exact time domain formulas for single-tone frequency estimation that trade a few extra calculations for improved noise robustness. Built from [1+cos]^k binomial weighting of neighbor-pair sums, the closed-form estimators are exact and are best evaluated at signal peaks for real tones, while complex tones do not share the zero-crossing limitation. Coefficients up to k=9 are provided.


In Search of The Fourth Wave

Allen DowneyAllen Downey September 25, 20214 comments

While working on Think DSP the presenter ran into a curious spectral pattern: sawtooth waves have all harmonics with amplitudes that scale like 1/f, square waves keep only odd harmonics with 1/f, and triangle waves keep odd harmonics with 1/f^2. That observation motivates a simple question: is there a basic waveform that has all integer harmonics but a 1/f^2 rolloff? The talk walks through four solution approaches, a fifth idea from the audience, and links to a runnable Colab notebook.


Approximating the area of a chirp by fitting a polynomial

Alexandre de SiqueiraAlexandre de Siqueira November 15, 20158 comments

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).


Candan's Tweaks of Jacobsen's Frequency Approximation

Cedron DawgCedron Dawg November 11, 2022

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.


Exact Near Instantaneous Frequency Formulas Best at Zero Crossings

Cedron DawgCedron Dawg July 20, 2017

Cedron Dawg derives time-domain formulas that yield near-instantaneous frequency estimates optimized for zero crossings of pure tones. Complementing his earlier peak-optimized results, these difference-ratio formulas work for real and complex signals, produce four-sample estimators similar to Turners, and cancel amplitude terms, making them attractive low-latency options for clean tones while warning they degrade in noise and at peaks.


A Lesson in Statistics Using Random Sequences

Neil RobertsonNeil Robertson March 14, 20267 comments

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.


Improved Three Bin Exact Frequency Formula for a Pure Real Tone in a DFT

Cedron DawgCedron Dawg November 6, 2017

Cedron Dawg extends his two-bin exact frequency formulas to a three-bin DFT estimator for a pure real tone, and presents the derivation in computational order for practical use. The method splits complex bin values into real and imaginary parts, forms vectors A, B, and C, applies a sqrt(2) variance rescaling, and computes frequency via a projection-based closed form. Numerical tests compare the new formula to prior work and show improved accuracy when the tone lies between bins.