Questions tagged [machine-learning]

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29 views

Using STFT as an input to a Neural Net

I'm trying to use the STFT as an input to a neural network. After flattening, there are over 4,000 features for a few seconds of audio. Is there a recommended way of summarising these to be a more ...
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8 views

FPR for time series of 1 hour epilepsy recording

I am working on epilepsy seizure prediction classification using a convolution neural network. My dataset consisting of multiple recording of each record for 1 hour, first I segmented each record into ...
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13 views

Use of spectrograms in using deep learning on EEG related problems

I am currently working on a classification problem related to EEG signals. My professor asked me to convert those signals into their spectrograms and try various convolutional neural networks on them. ...
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14 views

Feature Based Methods for Quality Inspection Problem

I am currently working on an image classification problem to classify thermal images (can be interpreted as false-color images) of certain products as with or without defect. From an initial search in ...
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1answer
37 views

a neural network approach for FIR filter

I am trying to write a code for a neural network to do the digital filtering on some signals. Is there any neural network model for digital filtering?
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25 views

Source Localization in the context of EEG

I am having difficulty understanding how source localization is used in Brain-Computer Interface (BCI) as a feature extraction method. As a bit of introduction, the measured activity (Matrix M) is a ...
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2answers
57 views

Help with denoising signal and periodogram analysis resources

This is a cross posting from the crossvalidated stack exchange as I thought this may be a better forum to ask. I have a dataset consisting of respiratory time series signals of different lengths ...
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1answer
160 views

Upsampling vs downsampling. Which to use when?

Downsampling reduces dimensionality of the features while losing some information. It saves computation. Upsampling brings back the resolution to the resolution of previous layer. My question is which ...
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27 views

Finding arbitrary/random repetitive patterns in signals (both self and across two signals)

I am trying to figure out a direction for my research. I need to find random repetitive patterns between two signals and on each individual signal. I have read about FFT and time series-motif ...
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0answers
22 views

interpreting the post filter features in a sensor data

I am new to signal processing and I am working on Filtring signals(using basic analog filters, FIR filters, and IRR filters), for Human activity recognition, using sensor data, I Extract the features ...
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0answers
12 views

Applying ICA on 3rd order cumulant

Background: I was reading the article Application of Higher Order Statistics for Atrial Arrhythmia Classification, and they mentioned using the higher order cumulant $$C_3^x = m_3^x(i, j)=E[x(n)x(n+i)...
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22 views

Which audio features to use for content based music recommendation

I am attempting to write a content-based music recommendation system using machine learning. Using a python library, I am able to extract the features from raw audio files. For each audio file, I have ...
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1answer
44 views

how to handle different durations of audio data?

I am new to signal preprocessing, I read about mel_spectrograms, MFCC's. Now I want to apply it and use the CNN model, But the data which I have for practice is having audio of different durations, ...
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1answer
52 views

Understanding noise removal method using wavelets

I am trying to understand how wavelet transform can be used to denoise a time series or signal and how to plot the scalogram image. My signal has a lot of fluctuations and as such I am finding it ...
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2answers
124 views

What is the current “state of the art” in future audio sample prediction, given recent developments in “image inpainting” using deep learning?

In the last few years, there have been many breakthroughs in the image processing world regarding repairing "damaged" images, images with corrupt pixels, or even reversing artefacts from ...
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50 views

DWT and FFT on a very low frequency signals

I am trying to extract features from a very low frequency signal of $0.1$ HZ and less than $100$ samples. Is it advisable to use FFT and DWT on this signal?
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24 views

multi-frame image restoration

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 approach would be best to teach ...
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2answers
141 views

Classic Signal Processing vs Deep Learning / Machine Learning (DNN / ML) Based Signal Processing

Are classic signal processing/statistics based approaches to optimum detection/estimation still relevant/important compared to ML based approaches using DL? There was a time when speech processing was ...
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1answer
25 views

Why not use synthetic datasets for training machine vision (deep learning) algorithms?

I am studying some examples of how to perform 3D instance segmentation in indoor scenes, and I have noticed many of the available datasets are from real environments. I was wondering with the ...
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1answer
55 views

Minimize the Cost Function of Values of Vectors Based on Their Amplitude

I have two vectors $X = [x_1,x_2,x_3,x_4]$; and $Y = [y_1,y_2,y_3,y_4]$; I know that $|x_1|$ = $|y_1|$, and $|x_2|$ = $|y_2|$,... so on. it means the difference is only in the sign. it might be ...
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1answer
23 views

Mathematics behind the creation of 3d face mask at runtime

I'm new in Image processing and Machine learning area. I want to create 3d mask of face at runtime. ...
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52 views

MWE of zero-sum mask in the context of machine learning

Federated Learning seems to have a lot of potential, I understand it can be done using different techniques, e.g. functional encryption, etc. The simplest seems to be zero-sum masks. For TensorFlow ...
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0answers
33 views

Why do people use STFT as a preprocessing step to using CNN?

Just briefly looking up some research papers on audio data and I have come across some papers that use STFT as a preprocessing step to using CNN. Why is this the case? What are the advantages and ...
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1answer
39 views

Automatic detection of noise-only segments in audio

This is my first question for this community. My connection to DSP comes via machine learning/deep learning, and I am working in the Python ecosystem. As a preprocessing step to audio classification, ...
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19 views

How can a CNN account for spectro-temporal constraints in neural data?

What are there the best ways to leverage the unique "geometrical" constraints of spectro-temporal signal representations (architecture, filter shapes, data augmentation, etc.)? For example, ...
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0answers
59 views

Hamilton-Jacobi-Bellman equation vs Riccati equation

Most of the literature on Reinforcement Learning discuss Hamilton Jacobi Bellman equations for optimality. In dynamics however Ricatti equations are used. I am curious if there are any parallels ...
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37 views

How to deal with different audio formats for audio classification?

I am working on an audio classification problem statement to classify between two audio classes. I have collected samples from jotform, they are providing audio widget to collect .wav audio but it ...
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1answer
148 views

Cochleagram vs STFT for CNN-based speech segregation

I’m working on a project (python-based) that would use ideal ratio masks (IRMs) as a basis for cleaning noisy speech in various environments. Specifically, this will be accomplished through the use of ...
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1answer
27 views

FFT question as it relates to Neural Networks / Supervised Learning Models

So I've been researching wavelet transforms and FFT. I want to feed wavelet transforms of a 1D signal in time into a neural net and train against a target variable at each time step. The idea being ...
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2answers
62 views

Understanding MFCCs

I am doing research about emotion recognition from speech, by applying machine learning. Most papers are recommending using MFCC features. Therefore, I am currently trying to understand the underlying ...
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0answers
208 views

How to save MFCC features and frame energy of several wav files to one .npz file for machine learning training?

I am creating a English-Italian corpus of around 100 hours of English audio from LibriVox aligned with their Italian textual translation. The alignment is at a sentence level and the corpus consist of ...
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37 views

Classifying motor imagery from EEG data: Feature selection

I am an undergraduate student who is trying to classify motor imagery from EEG data! I have no experience working with EEG or any neuroscience background, I only have a very basic knowledge of how ...
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0answers
54 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 ...
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0answers
74 views

How do i calculate the accuracy of an algoruthm?

I'm doing research on an machine learning image processing algorithm (segmentation algorihtm)i.e. computer vision performs when an image takes as an input and objects in an image are segmented and ...
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1answer
27 views

Using MFCCs for acoustic machine failure prediction

MFCCs are ubiquitously extracted for speech processing tasks, but I would like to know how suitable they are for non-speech processing tasks. Intuitively, it is my understanding that MFCCs are ...
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0answers
33 views

Is it useful to apply edge detection filter as a preprocessing step before applying CNN?

Background: my future boss would like me to apply a number of low level filters to industrial images before applying machine learning methods on them. From my knowledge this doesn't make any sense as ...
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16 views

How to update Kalman Filter with n-th order state translation?

In Kalman Filter, the hidden state translation is defined by $X_t=F_tX_{t-1}+W_t$, where $X_t$ can be a vector or a single value. This is actually derived from Bayes filter, in which 1-th order markov ...
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1answer
57 views
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65 views

Frequency contour detection in spectrogram

I have an image of a spectrogram and I wish to detect the tracks/contours of prominent frequencies present in the spectrogram. In the end, I want to be able to get various prominent curves from the ...
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1answer
47 views

How to prepare different input size in CNN

I'm doing a research about personality identification based on their signature using CNN method, however the learning feature for the personality traits have a different input size. I understand that ...
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1answer
128 views

Modeling audio effects, reverse engineering

Okay so I'm relatively new to signal processing and don't know the specific terminology to help narrow my search, but I'm looking for advice in the form of books, papers, references, etc that can help ...
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1answer
108 views

machine learning on multiple signal at once

I am very new signal processing and I am asking this with the expectation that someone gives me a concrete guideline on how to approach my problem. The problem I need to solve is that I have 2 ...
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1answer
59 views

Deep Learning: Classification vs. Convolution for Signal Restoration

Assume we have vector $X = [x_1, x_2, x_3, x_4 ,..... x_N], ∈ -1,1$. Therefore the value of $x$ is either 1 or -1. The vector $X$ is convoluted with random generated vector $Y$ whose length is the ...
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1answer
45 views

How to classify audio files based on their ZCR, energy, and enthropy of energy features?

Let's say I wanna classify the audio files of race car exhaust and normal car exhaust. I attain few features such as ZCR, energy and enthropy of energy from the training set and I wanna build the ...
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39 views

Deep Learning based NDA Channel Estimation

I was wondering if it is possible to use Deep Learning to estimate the Channel Impulse Response for NDA synchronization? I understand Deep Learning is not normally used for regression problems but I ...
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1answer
96 views

STFT to spectrogram

I would like to know whether I am correct in my understanding of going from STFT to a spectrogram. My goal is to convert a spectrogram back to a wav file. If I have my STFT: ...
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0answers
31 views

CWT coefficients as features for ML algorithms

I use CWT coefficients as features in ML algorithms and then I did the feature selection using the chi-square test but recently I figured out that the chi-square test can only be applied for ...
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0answers
15 views

How can I cluster signales by their different noise patterns?

Given be a set of signals (e.g. images) coming from one or more sources (e.g. different types of cameras) is it possible to find out, which signals come from which source? I consider this question ...
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40 views

Using unlabeled EEG data for Machine Learning

I am working on a project that is basically a game for motor-paralyzed people. It should take an EEG signal from FP1 channel of brain and then after processing it should generate command for the game ...
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47 views

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 ...