Discrete Updated 2025-07-16
Something that is very not continuous.
Notably studied in discrete mathematics.
Discrete Fourier transform Updated 2025-07-16
Output: another sequence of complex numbers such that:Intuitively, this means that we are braking up the complex signal into sinusoidal frequencies:and is the amplitude of each sine.
- : is kind of magic and ends up being a constant added to the signal because
- : sinusoidal that completes one cycle over the signal. The larger the , the larger the resolution of that sinusoidal. But it completes one cycle regardless.
- : sinusoidal that completes two cycles over the signal
- ...
- : sinusoidal that completes cycles over the signal
Motivation: similar to the Fourier transform:In particular, the discrete Fourier transform is used in signal processing after a analog-to-digital converter. Digital signal processing historically likely grew more and more over analog processing as digital processors got faster and faster as it gives more flexibility in algorithm design.
- compression: a sine would use N points in the time domain, but in the frequency domain just one, so we can throw the rest away. A sum of two sines, only two. So if your signal has periodicity, in general you can compress it with the transform
- noise removal: many systems add noise only at certain frequencies, which are hopefully different from the main frequencies of the actual signal. By doing the transform, we can remove those frequencies to attain a better signal-to-noise
Sample software implementations:
- numpy.fft, notably see the example: numpy/fft.py
DFT of with 25 points
. This is a simple example of a discrete Fourier transform for a real input signal. It illustrates how the DFT takes N complex numbers as input, and produces N complex numbers as output. It also illustrates how the discrete Fourier transform of a real signal is symmetric around the center point. Discrete Fourier transform of a real signal Updated 2025-07-16
See sections: "Example 1 - N even", "Example 2 - N odd" and "Representation in terms of sines and cosines" of www.statlect.com/matrix-algebra/discrete-Fourier-transform-of-a-real-signal
The transform still has complex numbers.
Summary:Therefore, we only need about half of to represent the signal, as the other half can be derived by conjugation.
- is real
"Representation in terms of sines and cosines" from www.statlect.com/matrix-algebra/discrete-Fourier-transform-of-a-real-signal then gives explicit formulas in terms of .
NumPy for example has "Real FFTs" for this: numpy.org/doc/1.24/reference/routines.fft.html#real-ffts
DFT of with 25 points
. Source at: numpy/fft_plot.py. This plot illustrates how the DFT of a real signal is symmetric around the middle point, and so only half of the transform points are needed to reconstruct the original signal. We also see how the phase of the sinusoids determines if their DFT components are real or imaginary. Discrete logarithm of the cyclic group Updated 2025-07-16
In this case, the problem becomes equivalent to reversing modular exponentiation.
This computational problem forms the basis for Diffie-Hellman key exchange, because modular exponentiation can be efficiently computed, but no known way exists to efficiently compute the reverse function.
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An algebra over a field where division exists.
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React setups:
DNA amplification Updated 2025-07-16
DNA amplification is one of the key DNA technologies:
- it is one of the main ways in which DNA detection can be done.
- it is the first step of Illumina sequencing, since you need multiple copies of several parts of the genome for the method to work
DNA detection Updated 2025-07-16
This can be used to detect if a given species of microorganism is present in a sample, and is therefore a widely used diagnostics technique to see if someone is infected with a virus.
You could of course do full DNA Sequencing to see everything that is there, but since it is as a more generic procedure, sequencing is more expensive and slow.
The alternative is to use a DNA amplification technique.
DNA replication is a key limiting factor of bacterial replication time Updated 2025-07-16
TODO confirm, but looks like it, e.g. E. Coli starts DNA replication before the previous one finished.
DNA sequencing Updated 2025-07-16
Big excitement picture at: molecular biology technologies.
DNS configuration of Ciro Santilli's website Updated 2025-07-16
AKA how this GitHub page gets served under the domain: cirosantilli.com
Ciro only touches this very rarely, and always forgets and go into great pain whenever a change needs to done, so it is important to document it.
The last change was of 2019-07-07, when Ciro moved from the www subdomain www.cirosantilli.com to the APEX cirosantilli.com. A redirect is setup from the www subdomain to APEX.
GoDaddy DNS entries:
Type Name Value TTL
A @ 185.199.108.153 1 Hour
A @ 185.199.109.153 1 Hour
A @ 185.199.110.153 1 Hour
A @ 185.199.111.153 1 Hour
CNAME www cirosantilli.github.io 1 HourMoved cirosantilli.com to Porkbun 2022-02, unfortunatly records were not automatically updated and domain went down for a bit, upadded to new entries for IPv6 as well which are not documented by GitHub:
TYPE HOST ANSWER TTL PRIORITY OPTIONS
A cirosantilli.com 185.199.108.153 600
A cirosantilli.com 185.199.109.153 600
A cirosantilli.com 185.199.110.153 600
A cirosantilli.com 185.199.111.153 600
AAAA cirosantilli.com 2606:50c0:8000::153 600
AAAA cirosantilli.com 2606:50c0:8001::153 600
AAAA cirosantilli.com 2606:50c0:8002::153 600
AAAA cirosantilli.com 2606:50c0:8003::153 600
CNAME www.cirosantilli.com cirosantilli.github.io 600where the IPs are obtained from: help.github.com/en/articles/setting-up-an-apex-domain#configuring-a-records-with-your-dns-provider (archive).
- Custom domain:
cirosantilli.com - Enforce HTTPS: checked
And the CNAME file is tracked in this repository: CNAME.
Docker (software) Updated 2025-07-16
Docker is good.
As a lightweight virtualization however, it does break more often than full proper virtualization like QEMU after some updates.
Does Stockfish use the GPU? Updated 2025-10-14
As of 2023, apparently does not use GPUs, but rather a deep learning algorithm called efficiently updatable neural network which is designed to run well on CPUs:
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There are unlisted articles, also show them or only show them.