Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [signal-processing]

Numerical analysis of a digitized signal

Signal processing refers to operations on the measurement and analysis of time and spatially varying signals where a signal is defined as a function that contains numerical information about the behaviour or attributes of some phenomenon.

While signals can be analog (i.e. continously measured quantities) the field is generally defined by the numerical analysis of digitally sampled signals, also referred to as digital signal processing (DSP).

Common applications of signal processing are in machine learning and communications.

References:

  1. Steven M. Kay, Fundamentals of Statistical Signal Processing, Volume 2: Detection Theory. ISBN-13: 978-0135041352
  2. Oppenheim, Alan V. Schafer, Ronald W. (1975). Digital Signal Processing. Prentice Hall. ISBN 0-13-214635-5.
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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 $$f(X_T) = y \in [1..K]\\ \text{for } X_T = (x_1, \dots, x_T)\\ \text{with } x_t \in \mathbb{R}^d ~,$$ via a global…
Emile
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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 interesting PDF entitled "Introductory overview…
Oren Hizkiya
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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 classify one-dimensional EEG signal? I am new to this…
Fazla Rabbi Mashrur
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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 change in chest expansion. I'd like compare the…
person157
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Smoothing time series data

I am building an android application that records accelerometer data during sleep, so as to analyze sleep trends and optionally wake the user near a desired time during light sleep. I have already built the component that collects and stores data,…
Jon
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detect number of peaks in audio recording

I'm trying to figure out how to detect the number of syllables in a corpus of audio recordings. I think a good proxy might be peaks in the wave file. Here's what I tried with a file of me speaking in English (my actual use case is in Kiswahili). The…
Eric Green
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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 statistical signal processing. But I am not sure how…
Tim
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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). My question is about the difference between the…
robin girard
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Dubious use of signal processing principles to identify a trend

I am proposing to try and find a trend in some very noisy long term data. The data is basically weekly measurements of something which moved about 5mm over a period of about 8 months. The data is to 1mm accuracey and is very noisy regularly changing…
Ian Turner
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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't think they have ever been recalibrated. I…
Junuxx
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What is a good way to measure the "linearity" of a dataset?

I have an empirically gathered dataset which relates two variables. Over a small range the relationship appears linear, however over a larger range there is clearly some second order polynomial relationship as can be seen in the image at…
user714852
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Pattern of mouse (or keybord) clicks and predicting computer user's activity

Based solely on the temporal pattern of mouse clicks (a list of click times $[t_1,t_2,t_3,\ldots]$), is it possible to predict the computer user's activity? For example out of: working vs spending time on Facebook vs watching photos vs playing a…
Piotr Migdal
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Are MFCCs the optimal method of representing music to a retrieval system?

A signal processing technique, the Mel frequency Cepstrum, is often used to extract information from a musical piece for use in a machine learning task. This method gives a short-term power spectrum, and the coefficients are used as input. In…
jonsca
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Boundary effect in a wavelet multi resolution analysis

What are the methods to minimize the effect of boundaries in a wavelet decomposition? I use R and the package waveslim. I have found for instance the function ?brick.wall but I am not too use how to use it. I am not sure the best solution is to…
RockScience
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Techniques for incremental online learning of classifier on stream data

Which may be good techniques to face this abstract problem? You have a data stream of a continuous signal, as one from a physical sensor. That signal has real (discretized) values, no attribute; addictional features (e.g., power, auto-correlation,…
stackovergio
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