Questions tagged [preprocessing]
Preprocessing is a relative term that usually refers to simpler operations applied to improve the operation of a more complex algorithm.
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CWT: selection of scales and filtering
I am using CWT to obtain scalograms of ECG signals as the one below:
In my research, most articles contain a pre-processing step before performing CWT (that usually includes signal normalization and ...
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Check whether signal is periodic
I have a signal with multiple frequencies. The frequency changes depending on the amount of air flowing through the fuel snap. The signal resembles a square wave ranging from $0.4$ to $4.5$ Volts and ...
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What are common pre-processing steps of EEG signals
I am new to EEG analysis, and I wonder what are the common pre-processing steps of EEG signals, for example, for motor imagery classification?
Currently, my pre-processing steps include
Epoch the ...
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Using readPLXFileC function in MATLAB for analysis on EEG
I am currently using a matlab function "readPLXfileC.c" to read plx data(of eeg) signal. Can anybody help me, how to do separate the channels, so that I can perform pre-processing on the ...
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Find rows that meet all criteria in SQL
I'm unable to create a SQL query that does the below:
Say for instance Person A participated in Event 1 and Event 2.
Person B participated in Event 1.
Person B participated in Event 1 again
Person C ...
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Creating Triangle Filters for Smoothing using Python
The 'binning' process consists in summing the energies (squared magnitude) within groups of adjacent FFT values. This will give you the total energy in a set of disjoint frequency bands.
A more ...
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Auditory models which are not human
I am doing a machine learning project and I'm interested in the different pre-processing techniques which can be applied to audio data. In particular, I am interested in comparing a human auditory ...
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magnitude spectrum
I have an ECQ signal of 360 Hz sampling frequency. I used an FFT to extract the frequency spectrum of my signal. Now I don't know exactly how to interpret this plot. How can I know the noise from ...
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Verification of intermediate outputs in Signal processing chain of FPGA
I have two ADC interfaces with FPGA and 32-bit processed output data from FPGA.
I have an IO signals to verify the Inputs and Outputs of FPGA.
But I dont have any test points to verify the ...
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Peak Sharping of multi-signal data
I have multi-signal data and as a processing step want to apply peak sharping of signal as shown in fig below.
is there any way I can achieve this in python ?
Literature :Paper 1(Peak sharping section ...
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Digital Signal Quantized Processor Complexity
In “traditional” digital signal processing, the complexity is computed as a number of multiplication the operation requires, e.g. the computation of the N-point DFT via the decimation-in-frequency FFT ...
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How to validate that an audio algorithm result is independent of microphone device?
I have a machine learning algorithm that takes speech sample audio recordings collected from mechanical Turk. During processing it was shown that some audio from certain OS/microphone devices have ...
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Pre-Processing Wi-Fi Channel State Information (CSI) Data
I was successfully able to collect some CSI data using the existing tool(s) on GitHub (https://github.com/StevenMHernandez/ESP32-CSI-Tool). The CSI data is a pair of imaginary and real number which ...
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My 3x3 Weighted Median Filter doesn't seem to be improving my image quality
In order to reduce noise in my training dataset,I attempted a WMF whose weights are shown in a 2-D array as follows(values finally get normalized by division by 15:
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How to detect offset that changes along time in a signal?
I have an issue that has to do with detrending a signal. First, it seems my signals behaves a little unusual (for me, I think). Some signals starts with a quite large offset, then it seems to ...
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Baseline correction for continuous EEG signals
I'm new to the topic so forgive the trivial question.
I am trying to understand data preprocessing for EEG signals. As I understand, after recording continuous EEG signals, they should be band-pass ...
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What's the purpose of augmenting an image with a random "gradient"?
I have the following Python code
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FFT response for noisy signal, averaging the response and
I try to analyze a system's state with acceleration sensors by measuring the frequencies and amplitudes.
Since a cheap sensor is used, I have a noisy signal in the beginning (up to 40Hz - see below). ...
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Measuring respiratory rate from a 3d accelerometer signal? How do I preprocess this data and move forward with it?
I have read a decent amount of papers that used wrist smartwatches to measure respiratory rate, or papers that used sensors attached to a persons chest. I can link them if it is necessary.
I am ...
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Detect Trigger in vibrational data
I'm trying to classify states with a 1D-CNN-Network structure. Therefore I need to analyze the incoming vibrational data in a certain window. Two examples of such signals are shown below.
I'm ...
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Help with automated baseline removal
This is more of a conceptual question, so apologies in advance if this is not the correct forum for such questions.
I am trying to find a repeatable and consistent method for removing the baseline of ...
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How should I remove obvious anomalies from spectral data?
I'm working with raman spectra and it seems that our spectrometer produces some anomalies at very specific wave numbers and I'm looking to remove them from the dataset. Here's a picture of 27 spectra ...
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How to apply baseline methods to MNE preprocessed raw EEG signals?
I am new at EEG preprocessing and classification. I have followed Clemens Brunner's blog https://cbrnr.github.io/2018/01/29/removing-eog-ica/ as a tutorial for MNE.
This is how I have preprocessed ...
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Upsampling and downsampling signals as a preprocessing step for a neural network
I have audio data acquired from a 4 channels sensors array.
As a preprocessing step for a neural network, I want to beamform and focus on the sound source. For higher resolution in the beamforming ...
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How to take inverse fft of windowed and callibrated fft data? [closed]
I have done windowing and fft on a signal but when I try to recover original raw signal ,I am unable to do it .Can anybody help me.
How to take inverse fft of windowed and callibrated fft data?
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Is sound the best way to transmit a signal under water?
Could sound be used in transmitting sound waves under water digitally? Could the sound then be converted by a repeater to transit by radio waves? What other ways can a signal be transmitted other than ...
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Frequency analysis to determine low-pass cut off frequency
I collected some data for a practical application, where the signal represents force data obtained from an impact of a punch against a force plate attached to a quasi-rigid rig (it moves once the ...
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Subtracting DC Offset a Complex Signal?
If I take the magnitude of a complex signal, and then subtract the mean amplitude, I remove DC offset but lose the real and imaginary components. How can I properly subtract the DC offset of a complex ...
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How do I know if my EEG signal need denoising?
I recently started working on sleep study.
For my research I download sleep EEG data from physionet. The EEG data has 100 Hz sampling rate and was recorded from 2 bipolar EEG site.
When I start the ...
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Calculating gyroscope data from accelerometer and attitude data
I am currently collecting accelerometer and attitude data using smartphone sensors. Data is collected at 100Hz over 2.5 seconds. Of which there are 250 accelerometer points and 250 points representing ...
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Does waveform-based ASR with lowpass filtering preprocessing still require the assumption of FFT?
I read some recent papers about time-domain speech recognition, and wondering if it steers away from the stationary assumption of FFT. However, some preprocessing operations like pre-emphasis and low-...
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The essential pre-processing steps in speech signal analysis
My question is that for simulating a new scheme for speech emotion recognition (feature extraction and classification), what are the necessary pre-processing steps (I mean any kind of normalization ...
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How to design bandpass filter in python when centre frequency is greater than sampling frequency?
I implemented basic bandpass filter using Scipy resource. But how to implement the same when signal is centred at non-zero centre frequency with centre frequency > sampling frequency.
I trying to ...
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For extracting the characteristics of the signal what minimum duration should be considered?
Being non signal processing student I have a limited understanding of concepts.
I have a continuous periodic bearing faulty signal of 10 seconds duration sampled at 12 kHz. So I have 120,000 ...
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correcting mirror ghosting effect
I have an application in which I have to process images taken through a mirror. The camera and mirror positions are fixed, and the object is always in the same position with respect to the mirror. The ...
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Separate key-related frequencies from audio signal
I have various samples of various instruments sound, and I'm trying to classify them using pyAudioAnalysis and various Machine Learning algorithms. The samples ...
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Artificial Neural Network Preprocessing in Real-Time Applications
I've come across an issue with my ANN when attempting to port my offline analysis to an online, real-time, application.
I currently train my algorithm using an array of input data, number of ...
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pre-emphasis with scaling?
I am working on speech synthesis with LPC and I originally implemented a pre-emphasis filter:
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pre-processing to improve feature detector before tracking
I am trying to make tracking for soccer player, I need to detect features from this player and then estimate the distance difference of these pixels over number of frames.
first I have to detect the ...
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Is this image good enough for OCR?
Hello I'm trying to ocr on a special image.
I've done adaptive threshold , polartocartesian transformation.
this is my original image
this is adaptive threshold
this is polartocartesian ...
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What is the difference between "preprocessing" and "normalization"?
I am currently writing my bachelors thesis about on-line handwriting recognition.
In this context, there are different methods to make the input data more useful to classifiers / to make learning ...
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Preprocessing audio signal for neural network classification
I need to identify certain features of the audio signal recorded from microphone in stethoscope. These sounds are only samples i've found, but the final signal will be probably a bit noisier (maybe ...
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select meaningful part out of a signal (for goertzel)
I have an on going input signal, most of the time with no activity.
Once in a while there is an activity (oscillations in different freq).
I need to take good 205 samples out of the signal.
what i ...
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Effect of different downsampling rate on EEG signal
I have a raw EEG signal of length 2,50,000 samples. I band passed it from 0.05-10Hz (sampling frequency=500). Then I down sampled it at 20Hz. Now question is: What will be effect if I vary down ...
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what are best features [closed]
I am doing OCR for Kannada and English. What are the best features in image? Please also tell me some tools to perform OCR before implementing it as code (like Rapiedminer for machine learning).
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Is it an excessive pre-processing step in image processing?
I wanted to consult with some experts whether or not this pre-processing step is excessive for what I'm trying to achieve. I am in a similar scenario as the author of the article, where I have many ...
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Should I consider rgb values of a pixel as one value?
I was reading this paper for a project work.
We train on 1.6 million 32*32 color images that have been preprocessed
by subtracting from each pixel its mean value over all images and then
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Why do envelope extraction before pitch detection?
I am referring to this report on pitch estimation.
The author does envelope extraction using Hilbert transform before applying AMDF.
What is the advantage of doing that?
Is speech a narrowband or ...
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voice recognition vs speech recognition MFCC
I have a basic understanding of the acoustic preprocessing involved in speech recognition: divide the speech into frames, find the mel frequency cepstral coefficients of each frame, construct a ...
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How to perform a Rubberband-Correction on spectroscopic data?
I basicaly understood how the Rubberband/Baseline-correction works.
The given spectrum is divided into (N) ranges.
The lowest points in every range are determined.
The initial baseline is built out ...
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