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.
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.
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.
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.
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.
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.
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.
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.
