Questions tagged [machine-learning]

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1answer
44 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 ...
5
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1answer
104 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 ...
4
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1answer
63 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 ...
5
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1answer
93 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 ...
5
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1answer
72 views

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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1answer
37 views

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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0answers
15 views

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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0answers
34 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 ...
4
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1answer
78 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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0answers
151 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 ...
5
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2answers
131 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 ...
2
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2answers
49 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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0answers
37 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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0answers
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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0answers
32 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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0answers
22 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 ...
4
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1answer
234 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 ...
4
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1answer
53 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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1answer
35 views

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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0answers
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. ...
0
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2answers
53 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 ...
1
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1answer
62 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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0answers
20 views

Measure of Separability for Classification Problems

Hello are there any methods, for a given set of features (possibly high dimensional) and labels (class 1 and class 0), to measure how "separable" the data is? E.g., if the problem was 2 ...
2
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2answers
99 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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0answers
13 views

Is my interpretation of CAR filter correct?

I am a computer scientist working on a Brain-Computer Interface (BCI) project. So, i am using EEG data from a dataset and classifying them with the use of machine learning algorithms. Initial results ...
0
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1answer
163 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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0answers
9 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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0answers
15 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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0answers
18 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 ...
1
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1answer
107 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?
3
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2answers
68 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 ...
2
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1answer
1k 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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0answers
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 ...
3
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1answer
114 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, ...
1
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1answer
77 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 ...
0
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2answers
137 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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0answers
58 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?
0
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0answers
29 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 ...
5
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2answers
363 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 ...
1
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1answer
34 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 ...
3
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1answer
72 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 ...
2
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2answers
39 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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0answers
61 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 ...
0
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1answer
64 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, ...
0
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0answers
22 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, ...
0
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0answers
106 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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0answers
45 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 ...
0
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1answer
362 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 ...
1
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1answer
30 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
112 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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