Hi. I'm new to GNU Radio but have experience with basic DSP (using
MATLAB for instance). Which blocks can I use to do these simple
tasks:
1. Convolution with an arbitrary (constant) wave in the time domain?
Example: I provide the wave as a fixed series of constants, I'd like
to convolute with it
The font size in GNU Radio Companion seems to be fixed and quite
small, at least for those with visual impairements. Is there any way
to change it (either via GUI or via a source edit)?
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I'm trying to demodulate AM (I know there are existing blocks to do
that, but I'd like to learn how to do it on my own).
In a real world analog circuit, I would find the envelope by first
rectifying the signal (using a diode), and then using a low pass
filter - that would give me the envelope.
Ho
/17/2013 11:01 AM, Robert James wrote:
>
>> I'm trying to demodulate AM (I know there are existing blocks to do
>> that, but I'd like to learn how to do it on my own).
>>
>> In a real world analog circuit, I would find the envelope by first
>> rectifying th
When I take a signal, stream->vector-->FFT-->IFFT-->vector->stream,
I'd expect to get the original signal back. Instead, I'm getting
something like the original signal, but following a very low frequency
carrier.
I thought this was due to the limits in vector size, but making this
very high (many
Is there a block that can set a threshold in the freq domain? That is,
any freq with less than x db should have no power whatsoever?
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FFT display, I see the carrier as a peak, and a long
thick band trailing off to the left.
I don't know how to measure the power - according to the FFT display,
it's not just at one freq, but trails off very far to the left.
>
> Greetings
> Marcus
>
> On 11/18/2013 03:4
I'm working on a series of blocks to measure the level of white noise
and attentuate it. (Yes, I know there are better ways of doing this,
like a Wiener filter - my goal here is to experiment and learn.)
Model: Assume white noise is present in equal power at all frequencies.
Plan:
Signal --> FFT
On 11/18/13, Tom Rondeau wrote:
> On Mon, Nov 18, 2013 at 8:22 AM, Robert James
> wrote:
>> On 11/18/13, Marcus Müller wrote:
>>> Hi Robert!
>>>
>>> This is strange -- but could be explained by the fact that numerical
>>> inaccuracy don't all
s the format?
On 11/18/13, Martin Braun (CEL) wrote:
> On Mon, Nov 18, 2013 at 08:29:02AM -0500, Robert James wrote:
>> I'm working on a series of blocks to measure the level of white noise
>> and attentuate it. (Yes, I know there are better ways of doing this,
>> like a
I believe the correct term for what I'm trying to find is PSD, which,
as far as I can tell (eg from here
http://www.mathworks.com/help/signal/ug/psd-estimate-using-fft.html ),
is well estimated using the FFT.
On 11/18/13, Robert James wrote:
> Thanks. Here's my understanding of FFT
it W-hat, that is within delta of x%
of Fourier coefficients, we assume W-hat is the value of the additive
white noise. Subtract W-hat from all the Fourier coefficients, IFTT,
and recover the signal with much of the white noise removed.
On 11/18/13, Martin Braun (CEL) wrote:
> On Mon, Nov 18,
Got it. I was assuming that since sinc looks like white noise, white
noise would look like sinc. That's not true - white noise is plain
ol' random.
Thank you everyone for the great discussion.
On 11/18/13, West, Nathan wrote:
> On Mon, Nov 18, 2013 at 11:25 AM, Robert James
&g
mapping
> from complex to real.
>
> Hope that helps a little bit :)
> Greetings,
> Marcus
>
> On 18.11.2013 18:25, Robert James wrote:
>> Got it: The Fourier coefficients tell you *two* things per freq:
>> amplitude and phase. In real values (what I'm used to), t
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