# Questions tagged [signal-processing]

Numerical analysis of a digitized signal

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### Features for time series classification

I consider the problem of (multiclass) classification based on time series of variable length $T$, that is, to find a function f(X_T) = y \in [1..K]\\ \text{for } X_T = (x_1, \dots, x_T)\\ \text{...
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### Application of wavelets to time-series-based anomaly detection algorithms

I've been beginning to work my way through Statistical Data Mining Tutorials by Andrew Moore (highly recommended for anyone else first venturing into this field). I started by reading this extremely ...
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### Is it a good idea to use CNN to classify 1D signal?

I am working on the sleep stage classification. I read some research articles about this topic many of them used SVM or ensemble method. Is it a good idea to use convolutional neural network to ...
25k views

### How can I align/synchronize two signals?

I'm doing some research but have come stuck at the analysis stage (should've paid more attention to my stats lectures). I've collected two simultaneous signals: flow rate integrated for volume and ...
• 223
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### What is the difference between functional data analysis and high dimensional data analysis

There are a lot of references in the statistic literature to "functional data" (i.e. data that are curves), and in parallel, to "high dimensional data" (i.e. when data are high dimensional vectors). ...
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### Dimensionality reduction of multiple signals using Fourier transform

I have $N$ recorded signals, $x$, each of which have been sampled 672 times across a time period of a week (= 15 min intervals). I will denote $x_{ij}$ as the $j$th sample for the $i$th recorded ...
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### Getting rid of spikes in sample data [duplicate]

Possible Duplicate: Simple algorithm for online outlier detection of a generic time series How could I get rid of sparky data in a descrete data set, but in a "smoother out" manner? Take for ...
• 101
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### Series dimensionality reduction for classification Input

I am looking to construct a predictive model where the outcome variable is binary and the input is time series. To make it more concrete, the model will predict if a customer churns (left the company; ...
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### Relations and differences between time-series analysis and statistical signal processing?

I was wondering what relations and differences are between time-series analysis and statistical signal processing? I found some recommendations of books in time series including some books in ...
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### How should I normalize my accelerometer sensor data?

I'm working with a large set of accelerometer data collected with multiple sensors worn by many subjects. Unfortunately, nobody here seems to know the technical specifications of the devices and I don'...
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### How to calculate the signal-to-noise ratio (SNR) in an image?

I am working with an image X, I apply the "adaptive median filter" in it and I get the image Y. I'd like to measure the SNR in both in order to evaluate the quantity of noise deleted. I know the ...
• 284
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### Trend Analysis of feature importance over time in R

I'm running an experiment on a Streaming Classification Model (an Online Random Forest) that I've created. If that is a completely foreign concept to you here is a presentation I did on it recently: ...
3k views

### Testing significance of cross-correlated series

I want to prove that, overall, signal B is correlated to signal A. I was thinking of using cross-correlation (in R) to measure this. Essentially I have two kinds of signals: signal A is a series of ...
• 415
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### Detect different fonts of audio from a single audio source

My code uses Google Voice API, to detect what one person said. For example, if I say one, two, three on my microphone the Google's API returns to me ...
• 166
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### Regression with repeated measures in Matlab

Is there a way to perform multiple logistic regression on repeated measures data using Matlab? I have a data set containing a daily measurement recorded from 20 participants for 60 days. I am ...
• 3,085
1 vote
675 views

### prediction on short time series with seasonality and data correlations

I have, say, 5 weeks of data standing for daily income of a company and I want to predict the next income. Obviously, there is a seasonality in data - every day is "seasonal" with the same day of the ...
• 133
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### Predictions for random walk in ARIMA model

Below I'm showing just a small subset of a larger set of measurements of a process that I'm using to in turn predict something else. The part of the process that is my signal of interest is the ...
• 1,211
150 views

### How to improve estimation of a deconvolved density

I have the following problem: Y = X + e with Y = Total reaction time (noisy signal) X = selection time (signal) e = discrimination time (noise) I am interestend in the distribution for X and ...
• 1,211
105 views

### Detecting the period of a signal with a length of only a few periods [duplicate]

Possible Duplicate: Fourier data with non-integer periods, correcting for phase bias I have a not perfectly but quit periodic signal, with a length of only a few periods. What methods are ...
• 1,118
1 vote
1k views

### Multiple peak fit - decomposing a graph into visible and hidden peaks of the same probability distribution

I have a graph as a set of coordinates (x, y), where x is a progressing time and y is proportional to an amount of molecules (chromatography results). Visible peaks on the graph look like of gamma ...
• 31
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### Encoding a time series with varying time differences as an image

There are methods to encode a time series into an 'image' i.e a matrix of scalar values. Some methods include recurrence plots, gramian angular field and markov transition field. Most methods assume ...
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