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Do I have to filter the whole (or at least a huge bit) of the signal every time a few new samples came in or is there a way (like the sliding DFT) where it is possible to efficiently determine the new part of the filtered signal? Digital filters don't work like that -- basically, classical FIR or IIR can work on every single new sample. You should really ...


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(Note: the paper pointed by hotpaw2's link is actually describing in more detail the algorthm I presented here) Consider a data window length of $N$ samples from $n=0$ to $n=N-1$. Let your original data window be $x_1[n]$, whose first sample is $x_{old} = x_1[0]$. Now your new data set is denoted as $x_2[n]$ whose samples are actually one sample left ...


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The algorithm for which you may be looking is called a "sliding DFT". For a small number of result bins, that number of "sliding Goertzel" filters can also be used. Here's one online description: https://www.dsprelated.com/showarticle/776.php of how to implement a sliding DFT. Basically, for each new sample, you add a new twiddle-multiplied vector to the ...


1

I think you are looking for a "peak" detectors. They are not filters in the conventional sense. Typically the output is increased when the incoming sample is either above a certain threshold or above the current output and decreased if it's smaller. The increase and decrease are often just simple exponential with time constants determined by your application....


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We do it in on a Windows platform with our Data Acquisition software - Dewesoft X. Some of our customers are using input signal and output it in around 10ms on Windows PC systems. Some of our DAQ devices have dual bus capability when one of the data buses is bypassing PC completely and send out data in real-time... The only downside is you need to use our ...


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I want to distinguish between harsh acceleration and normal acceleration as well as harsh braking and normal braking (or even coasting). On the basis of accelerometer readings, you could place thresholds on acceleration regions or look for outliers based on a profile of "normal" driving. A typical crash deceleration involves tens of gs (fig 7) and airbags ...


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The fundamental mechanics of performing real time digital auido processing under an X-windows based general purpose PC platform is based on using double-buffering family of architectures. In this architecture the sound that comes through a mic/line-in is first converted into samples via soundcard ADC and then it is filled into an input buffer at the user ...


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