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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Hypothesis testing on Probability of False Alarm

We have binary hypothesis testing problem as follows: $H_1$ (signal presence) : $y = s + n$ $H_0$ (signal absence) : $y = n$ Without loss of generality, to simplify the problem, let s be a constant ...
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Finding a Size Invariant Pattern in Noisy Data

I want to find similar patterns in my data, I assume that the patterns will be of different sizes both in time and in amplitude. The usual distance metrics will not work here, since the window size is ...
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How to calculate metacognitive efficiency when SDT is not applicable to the first order task?

I'm currently working on some data from an associative-memory study. Participants have to learn associations between stimuli from two different classes (1 and 2). As stimulus from class 1 is presented ...
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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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Applying ROC to evaluate time-series signal event picking model performance

I am trying to evaluate the performance of an event picking model that attempts to find the onset of a signal in a noisy time series. Data contains the true signal time (ground truth) and the ...
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Calculating d prime (d') using the Log-linear method (Hautus, 1995) in R

I have data from a memory test. I created a table with the absolute number of hits, misses, false alarms, and correct rejections. Each participant had 10 targets and 10 non-targets at each test (there ...
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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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Exclusion of participants based on sensitivity and criterion (SDT)

When I check the histogram of the participants' bias (measured by c), the distribution is right-skewed (i.e., more values are less than zero as expected). This indicates that the participants were ...
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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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1 answer
161 views

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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38 votes
3 answers
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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

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 negative, people who do not have that ...
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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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2 votes
1 answer
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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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Kurtosis to detect non-random signals in a spectrum

I have a spectrum that was created from a time series using the FFT. The spectrum has several man-made "channels" in it; some of these are one-bin wide, some are several adjacent bins wide (larger ...
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EEG waves measuring statistical significance of an event

I have recently gotten into a problem with EEG activity measurement. I need to prove (or disprove) that certain event triggered a statistically significant reaction in EEG activity. I know exactly at ...
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2 votes
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What is the distribution of $d'$?

In my experiment, repeated measures of $d'$ (computed from hit and false alarm rates) are computed for a small number of subjects (<10) under multiple (10) conditions. Primarily, I am interested to ...
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3 answers
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Confusion between true negatives and false positives (double negation?!)

Given the below term definitions ..my question is: why is the logical negation (opposite) of a false negative not a true negative? This would imply 1-α=β, which does not have to be the case. And ...
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Detecting a tremor given accelerometer data

I'm trying to figure out what technique to use in order to detect a tremor in accelerometer data. I have the acceleration in the x, y and z coordinates. I've plotted 4 graphs of this data below with ...
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Neural networks and signal-to-noise ratio

My guess is that neural networks do not work very well in noisy environments, i.e. the lower the signal-to-noise ratio, the worse the result of a neural network, if compared to other statistical ...
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