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Results tagged with signal-analysis
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user 80
The processing of signals for the purpose of extracting a parameter or property embedded in a signal. Signal goes in and far fewer numbers come out.
2
votes
Maximum of the sum of different sinusoids
As Hilmar says, you can get pretty loose bounds.
Might be better just to grind it out:
import numpy as np
from matplotlib import pyplot as plt
def calculate_signal(A, omega, phi, t):
if isinstanc …
- 26k
0
votes
Accepted
instantaneous frequency for a complex signal
This line
[f]=instfreq(lfm);
should be
[f]=instfreq(lfm)*fs;
If I do that and plot the true $\phi$ and the estimated $\phi$ then they overlap:
Code Below
clear all;
clc;
B=20e3;
fs=100e3;
T=10e-3 …
0
votes
How to find the pattern of a signal or main cycle of a signal?
For the second part, I'd just do the sum of absolute differences.
If I pull out this pattern:
and run this code:
pattern_to_find = data[117000:121000]
x = np.zeros(len(data))
for k in range(1,(len(da …
- 26k
5
votes
Accepted
How can we treat real signal as imaginary?
The MRI system is taking two sets of measurements: the in-phase and quadrature measurements. Both measurements are real. There is no way for a physical system to measure $i5 V$, we measure $5 V$.
The …
- 26k
1
vote
What is DC gain of sine wave multiple?
In addition to Dan's explanation, the other problem is that there are two impedances in parallel: the 4k$\Omega$ resistor and the 4k$\Omega$ in series with the capacitor. That means the overall imped …
- 26k
3
votes
Accepted
MUltiple SIgnal Classification (MUSIC) for Frequency Estimation
The second implementation takes account of the sampling frequency twice.
This line
freq_array = np.arange(-fs/2, fs/2, fs/nfft)
should be changed to
freq_array = np.arange(-0.5, 0.5, 1/nfft)
which t …
- 26k
5
votes
How to estimate the local trend in a signal?
Start simple: just use a 1-D median filter of an appropriate length.
If I do that with a length of 100 samples, I get the following for your first signal.
The top plot shows the original signal (blue …
- 26k
1
vote
Detecting outliers/noise from sensor data
For a higher tech approach, try the method in
P. Zheng, E. Chouzenoux, and L. Duval, "PENDANTSS: PEnalized Norm-Ratios Disentangling Additive Noise, Trend and Sparse Spikes," IEEE Signal Processing L …
- 26k
3
votes
Accepted
How to detect decrease of a digital signal?
I agree with Ben: use the CUSUM algorithm first up and see if that meets your needs.
If I do a rudimentary attempt at simulating your signal and implementing CUSUM, then I get the output shown below. …
- 26k
1
vote
Is there a formal definition of what it means for a signal to be sparse?
This page gives the following definition:
A signal is said to be sparse
if it can be represented in a basis or frame (e.g Fourier, Wavelets,
Curvelets, etc.) in which the curve obtained by plotting t …
- 26k
1
vote
Relationship between energy, power and sampling rate?
As rb-j alludes to in the comments, it's helpful to be clear about what is meant by energy.
When sampling a continuous-time signal, there is a time period between each sample: the sampling period.
For …
- 26k
0
votes
Method for splitting time-sampled signal into two signals
The usual way I'd think about approaching this sort of problem is to apply a Kalman filter.
The first step in applying a Kalman filter is knowing what the model for your signal is: Can you write down …
- 26k
2
votes
Why is ARMA preferred instead of AR?
An AR model takes the input $x[n]$ and generates the output $y[n]$ using only the present input and past computed outputs:
$$
y[n] = \sum_{k=1}^{K} a_k y[n-k] + b_0 x[n]
$$
An ARMA model allows the pr …
- 26k
1
vote
Doubt on Signal Processing Step
It's not clear what your code is doing, but my understanding is:
Delta = PresentSample * np.conj(PreviousSample)
gets the difference between the previous sample and the present one. This might look l …
- 26k
0
votes
Accepted
convert from binary to hexadecimal according to the algorithm "keeloq"
As per @tonys in the comments.
\begin{matrix}
1101 \ 1111 \ 1101 \ 1101 & \rightarrow& \mbox{inverted, bit reversed} & \rightarrow& \tt 0x04 \ 0x44\\
0001 \ 0111 \ 0001 \ 0111 & \rightarrow& \color{r …
- 26k