Questions tagged [1d]
12 questions
22
votes
4 answers
Fast / Efficient Way to Decompose a Separable integer 2D Filter Coefficients without the SVD
I would like to be able to quickly determine whether a given 2D kernel of integer coefficients is separable into two 1D kernels with integer coefficients. E.g.
2 3 2
4 6 4
2 3 2
is separable into
2 3 2
and
1
2
1
The actual…
Paul R
- 3,272
- 17
- 32
14
votes
13 answers
Deconvolution of 1D Signals Blurred by a Gaussian Kernel
I have convolved a random signal with a a Gaussian and added noise (Poisson noise in this case) to generate a noisy signal. Now I would like to deconvolve this noisy signal to extract the original signal using the same Gaussian.
The problem is that…
user1724
- 149
- 1
- 1
- 3
10
votes
1 answer
Solving a Convolution Problem of a 1D Signal
I'm finding in trouble trying to resolve this exercise. I have to calculate the convolution of this signal:
$$y(t)=e^{-kt}u(t)\frac{\sin\left(\dfrac{{\pi}t}{10}\right)}{({\pi}t)} $$
where $u(t)$ is Heavyside function
well I applied the formula that…
Mazzy
- 525
- 1
- 6
- 11
6
votes
4 answers
Deconvolution to Remove Gaussian Blur in 1D Signal (Wiener Filtering?)
I've got a set of biology data that I'm trying to denoise (effectively, a population statistic can only be measured convolved with a gaussian of known width)
My problem is this: I can measure (f*g), and I can measure g(x), but I need to know f(x).…
Abe Pressman
- 61
- 1
5
votes
1 answer
Deblurring 1D Data Using Direct Inverse Filtering
In my assignment I have been given recorded temperature over a period of time (193 Values) and the Impulse Response (5 Values with n=0 corresponding to the middle value).
data : data.csv | h = [1/16 4/16 6/16 4/16 1/16] | given question:
This is…
Mitul Agrawal
- 53
- 5
5
votes
4 answers
Algorithm for 1d spline interpolation suitable for 8 bit microcontroler
What is a concise, fast, down to earth algorithm for doing (or closely approximating) spline interpolation on a 1d continuous stream of data?
(Edit1: The paragraph below equates to saying "the data is uniform in interval." in an awkward way.)
The…
Charlie
- 193
- 8
4
votes
0 answers
Blind 1D equalization/deconvolution with some knowledge of filter kernel
Let $s_{\rm out}[n]$ be the 1D output signal of a system, $s[n]$ be the input, and $k[n,q]$ be the filter kernel for an element $n$ and for fixed value $q$. Then:
$s_{\rm out}[n] = s[n] \ast k[n,q]$
If I know $q$ as a real number, then I can…
Nicholas Kinar
- 943
- 2
- 8
- 15
2
votes
1 answer
Cross-correlation of time compressed 1D signal
If I ave 2 otherwise identical 1D signals that are phase shifted from each other then cross-correlation is a perfect way to identify the time lag between the 2 signals.
Now supposing I double the speed of one of those signals (eg sampled at every…
Goz
- 425
- 1
- 8
- 20
1
vote
1 answer
Way to extrapolate scarce signal
Firstly apologise if I use the wrong terminology, I don't have formal experience in signal processing, hence I would appreciate the help a lot.
I have a time-domain photon counting signal which due to experimental limitation has 256 time bins. This…
Isquare1
- 21
- 3
1
vote
2 answers
Detecting trough widths and locations in 1d signal
I have the following function obtained from averaging 2d camera image over one axis, where detection of aligned objects is desired:
I need to detect (roughly speaking) locations and widths of the troughs -- sometimes and object will be missing,…
eudoxos
- 165
- 6
1
vote
2 answers
Working with the DCT
I am having a very hard time to implement the DCT algorithm. I have quite a few requirements like it has to work with NxN matrix or at least power of 2, it has to be 2D, it has to produce same output as FFTW fftwf_plan_r2r_2d(FFTW_REDFT10) it has to…
Kachinsky
- 113
- 5
0
votes
2 answers
1D-Phase Unwrapping
I am new to signal processing and I am reading about 1D phase unwrapping
Here is the paper that I am reading.
It refers to x as the signal but then it shows in the graph the axis are origina phase in radians againts sample index. So is x the signal…
makala
- 33
- 3