Questions tagged [machine-learning]

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Why is automatic modulation classification hard?

There is a huge amount of research into automatic modulation classification (AMC) using machine learning.. Why is AMC a hard/difficult problem that we need to use machine learning or even deep ...
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Comparison of two ways of speaking

I have two audio files. The first one is like I would like to speak (reference). A little bit slower but the constant pace, good pronunciation, etc. The second one is various recorded audio files. I ...
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1 vote
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16 views

Standardize MFCCs Before or After Computing Deltas?

I want to create a feature space that includes MFCCs, MFCC deltas, and MFCC delta-deltas concatenated along the time axis which I will then feed into a CNN for speech emotion recognition. After ...
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30 views

How to decided the score threshold in speaker recognition?

I am new to speaker recognition and now starting from the GMM-UBM algorithm. Say I have a pre-trained UBM and speech from target speakers ...
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How to remove noise from audio and convert the audio to text

This is a video link https://www.youtube.com/watch?v=78YHir50N4o I have used the audio from this video. I am using SpeechRecognition library to transform it to text but because of the noise it is not ...
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0 votes
1 answer
28 views

How to modify spectrograms so that there is no effect of amplitude on their classification?

Is there any way to bring different classes of spectrograms to comparable amplitude levels so that when they are used for classification, the deep learning algorithm focuses on other aspects (like the ...
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7 votes
2 answers
563 views

A Machine Learning Based Algorithm as an Alternative to the Matched Filter

Consider we have to detect a known signal added with Gaussian noise. In this scenario, the matched filter is known to be an optimal filter for SNR. The question: is there any machine learning ...
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1 vote
2 answers
167 views

Mapping ground salinity in UAV images

I have a plant field with potatoes. I have made measurements on ground with a sensor and I have measured soil salinity (Electric Conductivity) and I have min EC and max EC. I have also UAV images of ...
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6 votes
1 answer
96 views

Classifying 2 Classes of Ultrasound Signal Using Machine Learning by Frequency Domain

I have two samples which, when exposed to ultrasound, emit their unique frequency responses. As can be seen in the attached figure, where the exciting frequency is 2.25 MHz, sample 1 emits a strong ...
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7 votes
1 answer
138 views

Building a Pipeline for Image Classification / Clustering Tasks with Features Extractor and Dimensionality Reduction (Example on MNIST Data)

In MNIST, there are 28x28 images of hand written digits. What features would one extract in order to classify then without any Deep Learning involved? How does Dimensionality Reduction get in the ...
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  • 389
6 votes
1 answer
152 views

Image Clustering Using Linear Discriminant Analysis (LDA) Compared to t-SNE / UMAP

This is a a continuation of the discussion from Unsupervised Clustering of Images. Image that we have MNIST database and we want to separate all the images like this. But we want to use Linear ...
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  • 389
4 votes
1 answer
135 views

Unsupervised Clustering of Images: Which Algorithms?

Given a set of images $ \left\{ \boldsymbol{x}_{i} \right\}_{i = 1}^{N} $ how could one cluster them in an unsupervised manner? What are the useful features / tools to do so? For instance, will ...
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5 votes
1 answer
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Image Segmentation Using Deep Learning

I see in many reviews on Autonomous Car how they segment the images with person, cars, etc... How is it achieved in Deep Learning? Could anyone give an example of that? How it is done?
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-1 votes
1 answer
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how would gradient descent work in optimizing a practical frequency response of a sinc function?

The gradient descent algorithm should work by minimizing the ripples in the stop and pass band, then increase the slope of the transition band. So basically the parameters of interest will be passband,...
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How do you find the length of a constant q transform window in librosa?

I am working on a machine learning project to transcribe classical chamber music. I have a collection of audio files and for each time interval, I have data which tells me which notes are being played....
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0 answers
74 views

How can i generate training progress plot from saved trained model in matlab?

I would like to know is there any ways to generate back the training progress plot or verbose result from the saved trained model if i forgot screenshot/save both data manually? the code that i use to ...
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4 votes
1 answer
85 views

Which Programming Language Should Be Used for Deep Learning (Deep Neural Network [DNN])?

I will do voice activity detection and speech enhancement based deep neural network. However, I don't know whether to do this via matlab or pyhton. In which programming language can I find more ready-...
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2 votes
0 answers
165 views

Can machine learning extract two source signals, given a mixed signal?

I have two signals from two sources at a given condition and I have a mixed signal at the same condition that I know is coming from those same two sources. Is it possible to extract the source signals ...
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6 votes
2 answers
223 views

Explain the Process of Spectral Pooling and Spectral Activation in the Context of CNN in Frequency Domain

I am reading the paper Design of an energy efficient accelerator for training of convolutional neural networks using frequency Domain Computation: which uses Frequency Pooling, from Spectral ...
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2 votes
2 answers
56 views

Cocktail Party Problem with a Single Signal of Data (Single Mic)

I have been doing some multimodal signal analysis, and sometimes ICA is used for detecting statistically independent components. From my understanding, say if you have 2 sources and 2 receivers/...
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43 views

I have two signals, recorded from the same device. How do I standardize/normalise them?

I essentially have two signals X and Y, recorded with PPG devices. These have been filtered already. I want to standardize(z-score) or min-max scale them but I don't know if I should do this on each ...
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0 votes
0 answers
21 views

Signal patterns between train and test sets are vastly inconsistent

I am trying to build a machine learning classification model of a given signal dataset of 3 classes (one file for train signal data is another one for test data). I tried different machine learning ...
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37 views

Is it possibel to use CNN to bandpass signal?

I have a time serie dataset and want to train a CNN-LSTM model to predict as well as detect outliers. How can I use CNN to filter the signal and extract features from specific frequency band?
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23 views

What image augmentations can help a neural network identify the lowest-value pixels within an image?

I am training a CNN to identify objects, and I believe the network will learn much faster if it can learn to focus on the pixels with the lowest value. One way to go about this would be to augment the ...
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5 votes
1 answer
362 views

Modern Method for 1D Signal Segmentation

I want to segment a signal in an unsupervised manner. The data is a 1D signal which has different segments which I want to be able to segment automatically for farther processing. I am looking for a ...
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5 votes
1 answer
63 views

The Meaning of $ \mathbb{E} $ Operator in the Pix2Pix Loss Formula of a Neural Network / Convolutional Neural Network

I've been observing the Pix2Pix Paper - Image to Image Translation with Conditional Adversarial Networks and wondered on formulas. For example, the objective of the CGAN is: , where x - observed image,...
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1 answer
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References of deep learning and ai for dsp researchers [closed]

Are there excellent references for machine learning, deep learning and ai for DSP researchers?
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1 vote
0 answers
19 views

Backpropagation in a Network [closed]

Hi does anyone know how to solve this. Im really struggling to figuring this one out. I am unclear of how the backpropagation part would work in this network and how to calculate it for each weight. ...
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0 votes
2 answers
74 views

Power Spectral Density as a single number confusion

I'm trying to recreate the results of a machine learning applied to the DSP classification in the article: link. I have a signal (activity measurements from a smartwatch) per patient, so about 30 ...
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  • 111
3 votes
1 answer
69 views

Can a linear reconstruction in compressive sensing perform well?

I am trying to implement compressive sensing for grayscale 2D images, then reconstructing them using a multi-layer perceptron(MLP). It seems to perform well no matter how many layers I add or remove, ...
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2 votes
2 answers
143 views

Recommendation for courses / studies on digital signal processing

I hold a master's degree in mechanical engineering. However at my job I am more and more diving into topics of signal processing and data science. I find it great to discover about new topics and to ...
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-1 votes
1 answer
270 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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1 vote
1 answer
187 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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3 votes
2 answers
77 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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2 votes
1 answer
2k 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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0 votes
0 answers
37 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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4 votes
1 answer
187 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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1 vote
1 answer
89 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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0 votes
2 answers
147 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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0 answers
69 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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30 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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6 votes
2 answers
549 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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1 vote
1 answer
38 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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4 votes
1 answer
76 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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3 votes
2 answers
42 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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1 vote
0 answers
78 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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0 votes
1 answer
70 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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0 votes
0 answers
23 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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0 votes
0 answers
117 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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0 votes
0 answers
55 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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