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I had heard that tape is still the best medium for storing large amounts of data.
well, "best" is always a reduction to a single set of optimization parameters (e.g. cost per bit, durability, ...) and isn't ever "universally true".
I can see, for example, that "large" is already a relative term, and for a small office, the ...
5
High-capacity tape formats use helical scanning. Here I look at why that gives a higher capacity than linear recording with four tracks (one stereo track on each side) like in a compact cassette (C-cassette).
Figure 1. Stereo C-cassette player/recorder linear head (left) and a helical scanning head from a data drive (right), same scale. There is a too-short-...
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First of all, welcome to DSP SE.
What you see in the image you have linked is termed (spectral) leakage. When you are dealing with the Fourier series you deal with a periodic continuous function which is "decomposed" into a (possibly) infinite sum (series). Then, when you go to the Fourier transform, you have a non-periodic function (which you ...
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You have already selected your answer, but I would like to put a few more lines.
First of all, objecting to Marcus, I think that your first assumption is correct! We can store one hour of almost CD quality (14-16-bits, 44100Hz, stereo) analog audio into these commercial music casettes; i.e magnetic reels. So on a very rough basis you have almost a 600 MB (...
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Typical cheap cassette tape recorders and players in the 1970's used audio circuitry that did not have a completely flat frequency response and added a lot of phase distortion (mostly inaudible to most consumers). In addition, the computers did not use high sample rate low quantization DACS and ADCs (which cost a fortune back then), sometimes only a simple ...
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It's almost a matter of philosophy, i.e., difficult to argue hard facts.
On the one hand all the features you mention can be extracted from the raw signals. So in theory the network should be able to learn how to do that if they provide meaningful information for the task at hand. This is what part of the ML community is claiming: feature engineering is dead,...
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Interesting code! This was tough to follow from the pictures, but I did run the OP's code from the linked site, I can't play the sound loud enough to really test but appears to not be very sensitive for lower volume signals. There is no indication of the frequency axis on the graphic but I assume the left side of the screen is DC and the right side of the ...
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In my workplace, with huge datasets, tapes are still in use for long term backup. Namely, one often uses Data8, a 8 mm Backup Format pionnered by Exabyte corporation.
Some history on tape formats: Much Ado About Exabyte/8mm Tape Drives.
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An IIR filter is a recursive one. It means, current value of output $y[n]$ is computed based on its previous value(s).
Consider a simple 1st order IIR filter definition:
$$y[n] = a \cdot y[n-1]+ b \cdot x[n]$$
$a$ and $b$ are the filter coefficients.
Now assume you have a long block of N samples input data. If you want to process that block of input data ...
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I haven't looked at the reference yet , but just to answer the question, yes filtering is performed prior to down sampling to avoid aliasing back in the out of band signals. However if your signal is already appropriately bandlimited you could forego the filter entirely. There's various reasons you might want to do other, unrelated, filtering after the ...
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Your question is an interesting project for you to research it on your own. Well, maybe with a little help from your friend and the SE community. And, as your question goes, start with generating samples from (1) a uniform distribution, and (2) a Gaussian distribution. I will accompany you in your first steps.
First, I generate waveforms of 1,048,576 samples ...
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