Questions tagged [signal-processing]

For questions about processing signals of any physical quantity, with the help of Machine Learning or Artificially Intelligent algorithms.

Filter by
Sorted by
Tagged with
1 vote
0 answers
7 views

Which neural network/ML framework to use for a partial amount of a fixed-time amount of sensor data?

Assume I've run a set of initial experiments. For each experiment, I have a set of input signals $I_e(i, t)$, and output signals $O_e(j, t)$ for $i \approx 10$, $j \approx 10$, and $0\leq t\leq t_{max}...
user avatar
0 votes
1 answer
28 views

What is the training accuracy of this model?

I’m trying to classifiy ECG signals using LSTM and MATLAB, the above plot shows that the training accuracy of the system is 100% but when I apply this code to calculate and get the accuracy I get only ...
user avatar
1 vote
0 answers
12 views

How can I learn to transform one input signal (time series) into another?

I'm posting this question here because I've been trying in vain to solve a problem for weeks and I hope some of you might have some useful suggestions. Basically, the problem is as follows. I have 7 ...
user avatar
0 votes
0 answers
21 views

Application of Spectral analysis in NLP

i want to know if there is any kind of relation between spectrl analysis methods and NLP(Natural Language Processing), for the demonostration purpose, let us implement little game : suppose we ...
user avatar
0 votes
0 answers
16 views

Given the high resolution signal and the low pass filter (kaiser filter), is there a way to reconstruct the low resolution signal?

When we upsampling a discrete 1d signal by 2x, we first interleave the signal by 0, then pass through a low pass filter. low resolution signal [x1, x2, x3, x4] -> interleave 0 -> [x1, 0, x2, 0, ...
user avatar
  • 101
1 vote
1 answer
74 views

How does using complex weights in a neural network affect performance?

If you switch a neural network from real weights to complex weights, you're roughly doubling the size of the network, and increasing the computational load by a factor of 2 to 4. My question is, in ...
user avatar
  • 150
0 votes
0 answers
71 views

Is it effective to use deep learning method to produce a 1D signal as output from a 2D image as input?

I have a 1D signal that will produce a 2D image after some image processing algorithm. Would it be possible and effective to use deep learning method to reproduce the 1D signal if I have the 2D image ...
user avatar
0 votes
0 answers
19 views

Model Architecture for Mapping Audio from Low-Quality Space to High-Quality

I am doing a side project, where I am planning on recording with a bad mic and a good mic concurrently, and am trying to make a model to map your low quality audio to the high quality space. First ...
user avatar
  • 111
1 vote
0 answers
42 views

How to detect the sine wave signal with different frequency using neural networks?

I'm wondering if there is a way to use a neural network that can detect the noisy sine wave, where the frequency is not constant. In other words, I'm not looking for a solution that would detect the ...
user avatar
  • 11
1 vote
0 answers
49 views

Can I call any function a signal?

While reading the Notation of the paper titled Geometric Deep Learning Grids, Groups, Graphs, Geodesics, and Gauges, I came across the following notations. $$ \...
user avatar
  • 3,201
1 vote
1 answer
52 views

Is it a good practice to pad signal before feature extraction?

Is padding, before feature extraction with VGGish, a good practice? Our padding technique is to find the longest signal (which is loaded .wav signal), and then, in ...
user avatar
  • 13
2 votes
0 answers
27 views

What are some of the main high level approaches to applying ML on kinematic sensor data?

I've just started a project which will involve having to detect certain events in a stream of kinematic sensor data. By searching through the literature, I've found a lot of highly specific papers, ...
user avatar
0 votes
0 answers
54 views

Deep Learning based image restoration using multiple frames

Suppose we have a sequence of still images each of which has been contaminated by some particles(ex, dust/sand/smoke) making the images very poor in certain areas. What architecture would be best to ...
user avatar
0 votes
1 answer
28 views

Which type of feature extractor do you suggest to classify sensor data?

I have IMU (Inertial Measurment Unit- 6 axis) sensor data. The sensor attached on a car and 7 different drivers wipe on same path. I want to extract features and classify drivers. Which type of ...
user avatar
  • 247
1 vote
0 answers
20 views

Feature extraction for exponentially damped signals

I am looking into exponentially damped signals where it is a stationary signal (after implementing the Adfuller statistical test) and I would like to look into how can I extract meaningful features ...
user avatar
6 votes
2 answers
2k views

Aren't all discrete convolutions (not just 2D) linear transforms?

The image above, a screenshot from this article, describes discrete 2D convolutions as linear transforms. The idea used, as far as I understand, is to represent the 2 dimensional $n$x$n$ input grid as ...
user avatar
1 vote
0 answers
33 views

What's the best method to predict/generate signal from one sensor (source) to signal from another another (target)?

I was wondering what is the best method out there to find relationship between two 1D signals so that I can predict/generate one (source) from the other (target). For example, let's say that in ...
user avatar
2 votes
0 answers
31 views

Determine Frequency from Noisy Signal With Neural Networks (With Adeline Model)

I'm trying to determine the frequency from a signal with NN. I'm using the Adeline model for my project and I'm taking a few samples in each 0.1-volt step in a true signal and a noisy one. First ...
user avatar
3 votes
1 answer
55 views

Analyzing vibration using machine learning

I would like a few suggestions on an idea that I have - I am trying to make a musical instrument (percussion), whilst just having a PVC disc. I am hitting the disc in a variety of styles (in order to ...
user avatar
0 votes
4 answers
163 views

How can I remove the noise from an EEG signal?

I am working on a project that takes signals from the brain, preprocesses them, and then makes the machine learn about what human is thinking about. I am struck on preprocessing the signal (incoming ...
user avatar
1 vote
1 answer
78 views

How can I combine the readings of multiple lidars into 1 point cloud? [closed]

I have a car with 8 lidars, each with a field of view of 60 degrees. My car looks like this: How can I merge all the lidar readings into 1 point cloud?
user avatar
3 votes
2 answers
347 views

Can a neural network be used to detect sine waves?

I am recording the vibrations of an AC Motor (50Hz Europe) and I am trying to find out whether it is powered on or not. When I record these vibrations, I basically get the vibration values ($-1$ to $+...
user avatar
  • 33
2 votes
0 answers
64 views

How can I detect fast and slow motion in videos?

I'm trying to detect if a given video shot is fast or slow motion. Basically, I need to calculate a "video motion" score in a given video sequence, meaning how fast or slow motion the video is. For ...
user avatar
  • 963
3 votes
2 answers
318 views

Can AI be used to reverse engineer a black box?

A while back I posted on the Reverse Engineering site about an audio DSP system whose designer had passed away and whose manufacturer no longer had source code (but the question was deleted). ...
user avatar
  • 131
1 vote
1 answer
3k views

What is a temporal feature?

What is a temporal feature, what features make something temporal in nature? Is this problem agnostic? How does it change from different fields of study?
user avatar
  • 71
9 votes
1 answer
13k views

Is it possible to clean up an audio recording of a lecture using some type of AI system?

Is it possible to clean up an audio recording of a lecture from a smartphone (i.e. remove the background noise) using some type of AI system?
user avatar
3 votes
2 answers
242 views

Can I reduce the "number of weights" in CNN to 1/3 by restricting the input as greyscale image?

In a CNN, does each new filter have different weights for each input channel, or are the same weights of each filter used across input channels? This question helps me a lot. Let, I have RGB input ...
user avatar
  • 89
4 votes
1 answer
500 views

Is there a way to perform pattern recognition without a labeled training set?

I have a 10GB file of a time series 1D signal. I want to find some patterns within this signal, I know CNN's are great for this but the problem is I don't have any training data. Now, I could, of ...
user avatar
  • 143
1 vote
2 answers
137 views

Is there a "better" (signal-based) language for artificial intelligence [closed]

I assume, there must be "signal-driven" and maybe also real-time programming language, which based on connectivy-data more than variables (int, string, etc). I would like to have a language without ...
user avatar
  • 69
9 votes
1 answer
367 views

How much of a problem is white noise for the real-world usage of a DNN?

I read that deep neural networks can be relatively easily fooled (link) to give high confidence in recognition of synthetic/artificial images that are completely (or at least mostly) out of the ...
user avatar
  • 271
1 vote
2 answers
150 views

Are there any studies which attempt to use AI to guess the human emotion based on the brainwaves?

Have there been any studies which attempted to use AI algorithms to detect human thoughts or emotions based on brain activity, such as using BCI/EEG devices? By this, I mean simple guesses such as ...
user avatar
  • 10.1k