Questions tagged [signal-detection]
Signal Detection Theory (SDT) explains how a receiver detects a signal in noise as a function of the receiver's sensitivity to the signal & the receiver's bias or tendency to assert the presence of the signal whether it is there or not.
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Can I fit a Poisson distribution to a continuous variable to apply event detection algorithm?
Preprocessing:
I have a time series of number of tweets per 10 minutes time interval that are all taken from a given discussion on a specific topic in a specific region. I preprocessed the data by ...
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Gaussian white noise model in application
I am interested in applications (to data) of non-parametric statistics, and my question concerned the Gaussian white noise model defined by,
$$
X_{t_1, \ldots, t_d}=f\left(t_1, \ldots, t_d\right) d ...
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Why do popular ML and statistical packages simply ignore classical estimation and detection algorithms for statistical signal processing? [closed]
For those who had a hard time to study and understand classical estimation and detection algorithms, and unfortunately realized that these algorithms are simply ignored by many packages that have the ...
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Is there a sense in which collections of probability distributions with the same matrix of Bhattacharyya coefficients are "essentially the same"?
A popular measure of "closeness" between probability distributions $\vec{p_1}$, $\vec{p_2}$ is the Bhattacharyya coefficient $\sum_j \sqrt{p_{1,j} p_{2,j}}$. Consider two statistical models $...
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If hypotheses get rejected, should one recraft the theoretical framework to better highlight the results or just report the results?
I developed a theoretical framework, based on signalling theory and further developed testable hypothesis. However, my hypotheses are rejected, results suggest the opposite. Countersignalling theory ...
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Do calculate SNR based on mean and stdev need normalization?
How to calculate Signal to Noise Ratio?
Is the mean to stdev ratio valid to be used as the basis for calculating SNR?
What if a dataset or sample has a value of 0 all then add 1 random value other ...
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How to predict signals in the A timeseries from other correlating timeseries B by using neural networks?
I have two time-series A and B that correlate in time, but not perfectly. The A time-series have real signal with 0 (no signal) or 1 (there is signal); durations of signal and no signal are semi-...
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Discovering alternative waveforms for Fourier transform (alternatives to sinusoidal waves)
I'm working on a classification algorithm that utilises a discrete Fourier transform on sensor data, as a means to detect the presence of an oscillating signal.
My issue is that the signal-generating ...
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Visualizing signal detection indices in r
I was wondering if any of you could help with how I can somehow plot result from a signal detection analysis in r? I have used the psycho package and calculated dprime, beta, aprime, bppd and c for ...
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Calculate probability of alarm and the posterior probability of this alarm being false over different frequencies of output
I have the following information for an automatic detection system that output a warning when a signal is detected:
Specificity: .99 (i.e. a false positive rate $FP = .01$)
Sensitivity: .9 (i.e. a ...
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Measuring response bias from a confusion matrix
Given a confusion matrix of a binary classifier, what are the best measures of response bias towards one of the classes?
One idea that comes to mind is Signal Detection Theory's criterion, but this ...
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What is the probability that multiple spectral lines are just noise?
In spectroscopy spectral line emissions are related to each other, with fixed widths and heights that correlate with all lines based on fixed physical conditions. If I detect one spectral line at a 3 ...
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Uncovering which frequencies two systems are communicating on by observing reoccurring time correlated signals and their frequencies
Suppose you have a set of communication systems {A, B, C, D}, which speak with each other as well as other systems not contained in the set. Our concern is how they speak with each other. They ...
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What are the effects on signal detection metrics when a base rate matching strategy is used?
Assume that:
We have two groups of observers
The base rate of the signal being present is 97%
Knowledge of this base rate is provided to observers in the second group
Group descriptions...
tends to ...
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Periods of High Activity Detection
So I have some sensor data (time series) of heart rate of some users. I want to detect the times they start and finish exercising.
The data is sensor readings of heart rate every second, it's ...
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Hypothesis testing for detecting signal in Gaussian noise
I have the following two hypotheses:
$\hspace{5cm}\mathcal{H}_0: y=w\\\hspace{5cm}\mathcal{H}_1: y=\sum_{i=1}^{N}h_ix_i+w$
Here $w\sim \mathcal{N}(0,1)$ represents Gaussian noise. $x_i \sim Bern(p), \...
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How to Add two white random gaussian noises from different noise sources?
I have generated two different white gaussian random noises in MATLAB using two different seeds. For example:
Asn1 = sqrt(noisepow1/2)* (randn(size(As))+1i*(randn(size(As))));
Asn2 = sqrt(...
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Track peaks of two or more moving pulse generators
I want to disentangle the signals of two or more moving pulse sources using recordings of these pulses (see pictures).
Example plots (4 panels per example to stretch the x axis a bit, the peaks of ...
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Detect regularity in arrival times
I am working with series of arrival times. My typical dataset is made of 20-100 samples.
I would like to detect regularity in the arrival time.
By regularity, I mean that the inter-arrival times may ...
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ROC curve as predictive tool in human performance--relationship between $\beta$, $X_C$, and signal probability
I am taking an engineering psychology course in which we are using ROC curves to evaluate human performance in signal detection. Many of the questions on this site about ROC curves are using them as a ...
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How can I "remove" variability in my data that is due to periodic signals, such as Temperature, RH and Solar radiation?
I have a measured signal that I know is affected by some periodic signals, such as Temperature, RH and Solar radiation.
Is there a way that I can "remove" their influence from my measured ...
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What are the parameters in signal recovery? Whether source of these parameters are the sampling property of impulse response?
I was reading the following book: Juditsky, Anatoli, and Arkadi Nemirovski. Statistical Inference via Convex Optimization. Vol. 69. Princeton University Press, 2020. Here, I could not visualize the ...
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Negative correlation between d' and hit rates?
I have data from a relatively easy task where subjects had to detect a signal in noise. I computed the hit and false alarm rates (HR, FAR), and then proceeded to compute d' using the standard formula, ...
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Minimum number of specimens for a medical experiment
Could someone validate the following - for the minimum number of specimens required.
A pathogen has 8 different forms.
Laboratory specimens (small organisms) are infected with the pathogen.
For ...
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How to identify the frequencies of periodic peak signals in a noisy time series? (with R)
Suppose to have two time series with peak signals at different frequencies, like these two:
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Fourier analysis to retrieve components of individual spectra
I have a basic, simple question, I am a physics student, and searching internet gives me a lot of signal processing theory but couldn't find this basic answer, which I plan to implement in my speech ...
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What percentage of a population needs a test in order to estimate prevalence of a disease? Say, COVID-19
A group of us got to discussing what percentage of a population needs to be tested for COVID-19 in order to estimate the true prevalence of the disease. It got complicated, and we ended the night (...
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Finding z score, based on knowing relative size of tails
(source: duckduckgo.com)
This is based on my looking into signal detection, which deals with two distributions, one "positive," in this case, people who have a certain disease, and one ...
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ROC curve, d' A' - assumption-free?
In my research I want to know how reliably certain feature of a sentence indicates the class that sentence belongs to.
So, according to that feature (=how many elements X they contain), the
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Finding exponential decay in noisy vibration signal
I have to analyse vibrational signals for which the general assumption is that there is one dominant excitation and an exponential decay in amplitude thereafter.
I have created smoothened envelopes ...
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How to deal with differently skewed biological data?
I have a single-cell data set with around 40 variables per cell (protein expression, all variables are measured simultaneously). The expression distributions for the single channels look quite ...
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Is signal detection theory a Bayesian approach?
Signal detection theory can be applied to modeling perception thresholds for defined stimuli, for example the detection of the presence of a specific signal. It is assumed both the stimulus intensity ...
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Signal Detection Theory: correct rejections - what underlying processes?
Suppose we have a word recognition task, on the basis of which we compute the four rates defined in Signal Detection Theory as Hits, False Alarms, Correct Rejections, and Misses (HR, FAR, CRR, MR). ...
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Chance&ceiling performance when using non-standardised hit&false-alarm rates
What is lost/missed out on if defining d', the sensitivity index from Signal Detection Theory, based on non-standardised rates?
For example, Patel et al. 2008, for a task where normal and anomalous ...
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What are the correct rejection- and miss-rate used for?
Say we have a two-alternative forced choice task on the basis of which we compute the four rates defined in signal detection theory, relating to hits, false alarms, correct rejections, and misses (HR, ...
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How does d-prime calculation relate to binomial mixed models with probit link?
for a study I tested participants in a same-different task (1AFC) about melodies. There were 3 versions of each melody (within-subjects factor "version").
So d-prime seems the natural response/...
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How do I calculate d' from experimental data?
In Signal Detection Theory, d' is defined by the z-scores of Hits and False Alarms:
d' = z(Hits) - z(False Alarms).
Say the task is to detect if a certain object is present in a series of pictures, ...
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Pointwise Mutual Information (PMI) and Information Component (IC)
Pointwise Mutual Information (PMI) and the Information Component (IC) formula (https://link.springer.com/article/10.2165/00002018-200225060-00002) seem to be the same, PMI is mainly used in natural ...
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Proving that a maximum exists when finding the optimal criterion in SDT
When deriving that there is an optimal criterion in the Signal Detection Theory literature that maximizes Proportion Correct (PC), we usually arrive at the following expression by setting the first ...
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Is there an accepted way to interpret d' (d-prime) for evidence of detection
I have run a learning experiment, with a yes-no familiarity test at the end, and computed d' across various conditions.
Is there some rule of thumb (perhaps dependent on sample size) as to how d' ...
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Why does d-prime of average hit and false alarm rates differ from the average d-prime of individual cases?
I'm reporting d-prime for a set of IDs. After setting a dprime() function, I use it to compute d-prime for each ID based on their hit and false alarm rates, saved ...
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A' (A prime) for extreme Hit rates and False Alarms
I am trying to compute the non parametric measure of sensitivity A' according to the following formula reported by Stanislav & Todorov (1999):
$$
A'= .5+sign(H-F)*((H-F)^2+abs(H-F))/(4*max(H,F)-4*...
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HMM depmixS4 using a vector of known states to fit model
I am using the depmixS4 package to fit HMMs to RNAseq count data.
My workflow is as follows:
Stack reads into a 'stack' vector which looks like this:
...
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What is a technique for extracting the data pattern from experimental replicates?
I collect the data of air pollution over the year. The data is 2D where the first axis is discrete scale (mass of pollutants in integer; 50, 51, 52...) and another axis is continuous scale (intensity)....
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Hit-&false-alarm-rates: cases of undefined denominator
I wish to apply SDT for an experiment whereby, while listening to a piece of music, subjects were asked to press a key when detecting a certain cue in the music. Based on the parts of the piece where ...
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Computing z-scores for hit & false-alarm rates in Signal Detection Theory
For each subject in my sample, I need to compute a sensitivity index, d-prime, defined in Signal Detection Theory as
d' = z(HR) - z(FAR)
where HR and FAR are the ...
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Building Neyman-Pearson test in 2D-space having only data for $H_0$ and $H_1$
Suppose we have some statistical data which is points in 2D-space. More precise sample space is upper right quarter of $\mathbb{R^2}$:
$$\Omega = \{X | X=(x_1, x_2),\, x_1, x_2\in \mathbb{R_+}\}$$
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How can I best determine the Signal/Noise of a pulsed signal?
I have this pulsed signal, and I would like to quantify the signal to noise ratio. Is there a preferred way to do this? My current approach is to filter the points that are obviously part of the ...
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How to obtain a signal/noise measurement from a video without a background control
I have a video with a periodic process that can be seen as a change in brightness of the frame. I am measuring the process by calculating the average brightness value of the frame and plotting it over ...
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Negative D-prime values; use absolute values?
I have calculated D-prime measurements for for a memory performance task. Subjects viewed images that were either old or new and had to indicate their response via a button press. Thus, their response ...
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