Energy Detection Model Research Articles

The influence of temporal features of the signal on detectability: Data and signal-detection analyses

Dave Green had an enormous influence on auditory research via signal-detection theory. A major contribution of signal-detection theory is the concept and application of the ideal detector, which establishes the absolute optimal detection performance. To bridge between the ideal performance and the less-than-ideal human performance, Green and Swets (1966) described an energy detector. The energy-detector model relaxed assumptions of the ideal detector to account for the phase insensitivity and limited frequency selectivity of humans, but it retained the assumption that the time window is matched to the signal duration. However, the time-window assumption had no clear support from human data. To help fill this gap, we examined the detectability of signals with expected versus unexpected temporal properties. The results of experiments and signal-detection analyses suggest that listeners listen selectively to signal duration, implying that they match the time window to the overall signal duration as was assumed in the energy-detector model. Additional results suggest that listeners do not also listen selectively to the temporal structure of the signal, implying that the temporal constraint is based on overall signal duration. We are grateful for the opportunity to have worked with Dave.

Humans attend to signal duration but not temporal structure for sound detection: Steady-state versus pulse-train signals

Most sounds fluctuate in amplitude, but do listeners attend to the temporal structure of those fluctuations when trying to detect the mere presence of those sounds? This question was addressed by leading listeners to expect a faint sound with a fixed temporal structure (pulse train or steady-state tone) and total duration (300 ms) and measuring their ability to detect equally faint sounds of unexpected temporal structure (pulse train when expecting steady state) and/or total duration (<300 ms). Detection was poorer for sounds with unexpected than with expected total durations, replicating previous outcomes, but was uninfluenced by the temporal structure of the expected sound. The results disagree with computational predictions of the multiple-look model, which posits that listeners attend to both the total duration and temporal structure of the signal, but agree with predictions of the matched-window energy-detector model, which posits that listeners attend to the total duration but not the temporal structure of the signal. Moreover, the matched-window energy-detector model could also account for previous results, including some that were originally interpreted as supporting the multiple-look model. Taken together, at least when detecting faint sounds, listeners appear to attend to the total duration of expected sounds but to ignore their detailed temporal structure.

Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules

&lt;span&gt;The performance of a cognitive radio network (CRN) mainly depends on the faithful signal detection at fusion center (FC). In this paper, the concept of weighted Fuzzy rule in Iris data classification, as well as, four machine learning techniques named fuzzy inference system (FIS), fuzzy &lt;em&gt;c&lt;/em&gt;-means clustering (FCMC), support vector machine (SVM) and convolutional neural network (CNN) are applied in signal detection at FC taking signal-to-interference plus noise ratio of secondary users as parameter. The weighted Fuzzy rule gave the detection accuracy of 86.6%, which resembles the energy detection model of majority rule of FC; however, CNN gave an accuracy of 91.3% at the expense of more decision time. The FIS, FCMC and SVM gave some intermediate results; however, the combined method gave the best result compared to that of any individual technique.&lt;/span&gt;

Performance of Threshold Detection in Cognitive Radio with Improved Otsu’s and Recursive One-Sided Hypothesis Testing Technique

Cognitive radio (CR) is a new technology proposed to enhance spectrum efficiency by enabling unlicensed secondary users to access the licensed frequency bands without getting involved with the primary users licensed. Although considered optimal, in order to calculate the signal threshold, this approach requires prior noise statistics information. Even though considered optimal, in order to calculate the signal threshold, this approach requires prior noise statistics information. A prominent example of an Adaptive Threshold Estimation Technique (ATT) for energy detection in Cognitive Radio (CR) is the Recursive One-sided Hypothesis Testing Technique (ROHT). Accurate threshold values are known to be calculated based on the correct choice of their parameter values, which include the standard deviation coefficient and the stop criteria. In this paper, for efficient threshold estimation, the improved Otsu and ROHT are combined for estimating threshold even in the presence of noise floor without need of prior knowledge. The proposed methodology for enactment in cognitive radio sensor networks (CRSN) system based on the adaptive threshold energy detection model with noise variance estimation. The simulation is carried out with the help of Matlab 2017a with the improved Otsu and ROHT techniques. The results obtained shows that improved Otsu and ROHT techniques outperforms that of fixed threshold energy detection in terms of different probability of false alarm rates and miss detections

Energy-efficient service-oriented architecture for mobile cloud handover

Mobile cloud computing uses features to deliver outsourcing data to remotely available mobile devices. However, the flexible nature of the mobile device is a critical challenge for the mobile cloud computing environment. The mobile phone significantly degrades the data transfer performance when initiating the handover process. Thus, an energy-efficient handover process could improve the quality of service (QoS). Here, we introduce a secure energy-efficient and quality-of-service architecture (EEQoSA) for the handover process in the mobile cloud computing environment. The proposed architecture involves four layers: application, the Internet protocol multimedia subsystem (IPMS), communication, and media with connectivity layers.These four layers collectively handle the energy-efficiency, security and QoS parameters. Existing service-oriented architectures designed for mobile cloud computing are based on the symmetric encryption cryptography to support different media services. However, this approach easily allows an adversary to expose the symmetric key and gain access to private data. Thus, our proposed architecture uses the secure and strong authentication (SSA) process at the IPMS layer by protecting the media services from unauthorized users, as the IPMS is the central layer that could be the entry point for an adversary. Furthermore, to extend the mobile lifetime during the handover process, an energy detection (ED) model is deployed at the communication layer to detect the energy level of the mobile device prior to the handover initialization process. The media with the connectivity layer supports the secure handover process using a priority enforcement module that allows only legitimate users to complete the re-registration process after initiating the handover. Finally, the architecture is tested using the CloudSim simulation environment and validated by a comparison with other known service-oriented architectures.

Secure and quality-of-service-supported service-oriented architecture for mobile cloud handoff process

Mobile Cloud Computing (MCC) combines the features of mobile computing, cloud computing, and wireless networks to create the healthy computational resources to mobile cloud users. The aim of MCC is to execute the highly attractive mobile applications on a plethora of mobile cellular telephones, with highly rich user experience. From the perspective of mobile computing, Quality of Service (QoS) provisioning depends on the efficiency of the handoff process. Thus, it is highly important to introduce an energy efficient and secure handoff process to improve the performance. In this paper, we propose a Secure Seamless Fast Handoff (SSFH) scheme to improve the energy efficiency and the QoS in the MCC. The proposed scheme consists of four layers: application layer, service layer, infrastructure layer, and media layer. These four layers collectively handle the security, energy-efficiency, and the QoS. Existing service-oriented architectures designed for the MCC are based on the symmetric encryption protocols to support the application layer. However, it is much easier for an adversary to expose the symmetric key and gain access to the confidential data. The application layer is secured using a combination of both attribute-based encryption and an asymmetric encryption cryptography. To extend the mobile lifetime, energy detection (ED) model is deployed at the infrastructure layer to detect the energy level of the mobile devices prior to the pre-registration process. Furthermore, a dual authentication process is performed on the service and at the application layer to minimize the possibility of identity-high jacked or impersonation attack. The media layer supports the secure handoff process using policy enforcement module that allows only legitimate users to complete the re-registration process after initiating the handoff. Thus, a significant amount of the bandwidth and energy could be preserved. Finally, the secure service-oriented architecture is programmed using C++ platform and the results are compared with other well-known existing service-oriented architectures. The experimental results confirm the validity and the effectiveness of our proposed architecture.

One-Bit Hard Combination Decision Scheme for Cooperative Spectrum Sensing in Cognitive Radio

&lt;p&gt;In this paper, the performance of 1-bit hard combination decision scheme for cooperative spectrum sensing in Cognitive Radio has been studied to maximize the probability of primary user detection. Energy detector model is used to observe the presence of primary user signal. Simulation result shows that the probability of missed detection is decreasing for both conventional and 1-bit hard combination OR rule with increasing the probability of false alarm correspondingly. It also has demonstrated that 1-bit hard combination decision scheme exhibits comparable performance with the conventional one-bit scheme and thus achieves a good tradeoff between performance and complexity.&lt;/p&gt;

Simulation of image detectors in radiology for determination of scatter‐to‐primary ratios using Monte Carlo radiation transport codeMCNP/MCNPX

The purpose of this study was to compare and validate three methods to simulate radiographic image detectors with the Monte Carlo software MCNP/MCNPX in a time efficient way. The first detector model was the standard semideterministic radiography tally, which has been used in previous image simulation studies. Next to the radiography tally two alternative stochastic detector models were developed: A perfect energy integrating detector and a detector based on the energy absorbed in the detector material. Validation of three image detector models was performed by comparing calculated scatter-to-primary ratios (SPRs) with the published and experimentally acquired SPR values. For mammographic applications, SPRs computed with the radiography tally were up to 44% larger than the published results, while the SPRs computed with the perfect energy integrating detectors and the blur-free absorbed energy detector model were, on the average, 0.3% (ranging from -3% to 3%) and 0.4% (ranging from -5% to 5%) lower, respectively. For general radiography applications, the radiography tally overestimated the measured SPR by as much as 46%. The SPRs calculated with the perfect energy integrating detectors were, on the average, 4.7% (ranging from -5.3% to -4%) lower than the measured SPRs, whereas for the blur-free absorbed energy detector model, the calculated SPRs were, on the average, 1.3% (ranging from -0.1% to 2.4%) larger than the measured SPRs. For mammographic applications, both the perfect energy integrating detector model and the blur-free energy absorbing detector model can be used to simulate image detectors, whereas for conventional x-ray imaging using higher energies, the blur-free energy absorbing detector model is the most appropriate image detector model. The radiography tally overestimates the scattered part and should therefore not be used to simulate radiographic image detectors.

Applications of psychophysical models to the study of auditory development

Psychophysical models of listening, such as the energy detector model, have provided a framework from which to characterize the function of the mature auditory system and to explore how mature listeners make use of auditory information in sound identification. The application of such models to the study of auditory development has similarly provided insight into the characteristics of infant hearing and listening. Infants intensity, frequency, temporal and spatial resolution have been described at least grossly and some contributions of immature listening strategies to infant hearing have been identified. Infants psychoacoustic performance is typically poorer than adults under identical stimulus conditions. However, the infant’s performance typically varies with stimulus condition in a way that is qualitatively similar to the adult’s performance. In some cases, though, infants perform in a qualitatively different way from adults in psychoacoustic experiments. Further, recent psychoacoustic studies of children suggest that the classic models of listening may be inadequate to describe the children’s performance. The characteristics of a model that might be appropriate for the immature listener will be outlined and the implications for models of mature listening will be discussed. [Work supported by NIH grants DC00396 and by DC04661.]

Stochastic resonance in psychophysics and in animal behavior.

A recent analysis of the energy detector model in sensory psychophysics concluded that stochastic resonance does not occur in a measure of signal detectability ( d'), but can occur in a percent-correct measure of performance as an epiphenomenon of nonoptimal criterion placement [Tougaard (2000) Biol Cybern 83: 471-480]. When generalized to signal detection in sensory systems in general, this conclusion is a serious challenge to the idea that stochastic resonance could play a significant role in sensory processing in humans and other animals. It also seems to be inconsistent with recent demonstrations of stochastic resonance in sensory systems of both nonhuman animals and humans using measures of system performance such as signal-to-noise ratio of power spectral densities and percent-correct detections in a two-interval forced-choice paradigm, both closely related to d'. In this paper we address this apparent dilemma by discussing several models of how stochastic resonance can arise in signal detection systems, including especially those that implement a "soft threshold" at the input transform stage. One example involves redefining d' for energy increments in terms of parameters of the spike-count distribution of FitzHugh-Nagumo neurons. Another involves a Poisson spike generator that receives an exponentially transformed noisy periodic signal. In this case it can be shown that the signal-to-noise ratio of the power spectral density at the signal frequency, which exhibits stochastic resonance, is proportional to d'. Finally, a variant of d' is shown to exhibit stochastic resonance when calculated directly from the distributions of power spectral densities at the signal frequency resulting from transformation of noise alone and a noisy signal by a sufficiently steep nonlinear response function. All of these examples, and others from the literature, imply that stochastic resonance is more than an epiphenomenon, although significant limitations to the extent to which adding noise can aid detection do exist.

Spectral integration in bands of modulated or unmodulated noise

Spectral integration was measured for pure-tone signals masked by unmodulated or modulated noise bands centered at the signal frequencies. The bands were typically 100 Hz wide, and when modulated, they were sinusoidally amplitude modulated at a rate of 8 Hz and a depth of 100%. In experiment 1, thresholds were first measured for each individual pure tone of a triplet in the presence of its respective masker band, and then for those three tones added together at their respective threshold levels, masked by their respective masker bands. Four sets of triplets were used: 250, 1000, 4000 Hz; 354, 1000, 2828 Hz; 500, 1000, 2000 Hz; and 800, 1000, 1200 Hz. When the masker bands were unmodulated, the amount of spectral integration was about 2.4 dB for all triplets, consistent with the integration expected based on the multiband energy detector model. When the bands were modulated, the amount of integration depended upon the spacing between masker bands; for the two widest spacings, the integration was between about 0 and 3 dB, whereas for the two closest spacings, the integration was approximately 5 dB. Experiments 2 and 3 addressed the cause of this greater spectral integration in the presence of the modulated masker bands with closer spacing. The second experiment demonstrated that sensitivity (d') was proportional to signal power regardless of whether the background noise was modulated or not, and thus the greater integration in dB in the presence of the modulated noise bands could not be accounted for by shallower psychometric functions in those conditions. Instead, the third experiment showed that the greater integration was likely due to the fact that the masker bands were comodulated. In other words, it was probably due to cues related to comodulation masking release when all three bands (and signals) were present.

Effects of signal duration on the recognition of masked communication signals by the grasshopper Chorthippus biguttulus.

The detection and recognition of acoustic communication signals masked by noise was investigated in a grasshopper (Chorthippus biguttulus) whose auditory system exhibits only poor spectral resolution and therefore has to operate in the time domain. The signals of this species consist of numerous identical subunits that enable the receiver, in principle, to make repetitive measurements. We aimed at determining the maximum integration time in this species by using stimuli of different durations under increasing noise levels. As a criterion for recognition the typical phonotactic turning response of the males was evaluated, which is reliably triggered by a female song, and thus is a sensitive indicator for recognition of conspecific signals. When confronted with a long signal (1000 ms) males tolerated a 2.4 dB higher noise level as compared to a short signal (250 ms). Noise tolerance improved with increasing signal duration from 250 ms to 450 ms. Beyond this signal duration, however, no further improvement was observed, indicating an upper limit for temporal integration that corresponds to only five song subunits. The gain in noise tolerance had a slope of 2.7 dB per doubling duration, which corresponds to the expectation derived from an energy detector model (3 dB per doubling duration) rather than to the value expected from signal detection theory (1.5 dB per doubling duration).

Stochastic resonance and signal detection in an energy detector--implications for biological receptor systems.

Stochastic resonance is demonstrated in a simple energy detector model, as a non-monotonic relationship between signal-to-noise ratio and detection of a sinusoid signal in bandpass-limited Gaussian noise. The behaviour of the model detecting signals of various intensities and signal-to-noise ratios was investigated. Significant improvement in detection was obtained by adding noise for mean signal intensities below the detection criterion of the detector. The range of usable noise levels, however, may be too small to be biologically meaningful. It is demonstrated that improving detection in the analysed model by adding noise to an otherwise undetectable signal is only at best as efficient as what can be obtained by adjusting the criterion to the signal-to-noise ratio. Improving detection by means of stochastic resonance is thus a sub-optimal strategy. It is speculated whether a demonstration of stochastic resonance in a biological system indicates any adaptive significance. More than anything, it indicates the presence of a mismatch between receptor sensitivity and the signal-to-noise ratio of the experiment, not the cause of this mismatch.

Psychometric functions for gap detection in a yes-no procedure.

To examine models of temporal resolution and to investigate the decision processes underlying the detection of a brief pause in a bandpass noise, psychometric functions for gap detection were measured at octave frequencies from 0.25 to 8 kHz. Three normal listeners were tested using a constant-stimulus procedure with a cued Yes-No paradigm. The Minimum Detectable Gap (MDG) estimated from the midpoint of the psychometric functions decreased systematically with increasing frequency. The slopes of the psychometric functions generally increased as the test frequency increased up to 2 kHz, but remained constant at the higher frequencies. Two models were investigated: an energy-detector model and a loudness-detector model. Both consisted of auditory filtering, a nonlinearity, and short-term integration. In the energy-detector model, the nonlinearity was a square law. In the loudness-detector model, it was a compressive power law. Using the usual Gaussian approximations, the energy-detector model fails at low frequencies because the probability distributions of short-term energy differ from Gaussian distributions. The probability distributions of short-term loudness closely follow Gaussian distributions. The loudness-detector model predicts the frequency dependence of the MDG quite accurately, except at 0.25 kHz. It also predicts psychometric functions that resemble the data at low frequencies, but the predicted slopes increase much less with frequency than the measured slopes. This result may indicate that the onset response to the trailing marker of the gap provides an important cue for detection of gaps with durations exceeding the MDG.

Receiver operating characteristics and temporal integration in an insect auditory receptor cell

Receiver operating characteristics (ROC) analysis was applied to the problem of temporal integration in the A1 auditory receptor of the noctuid moth Noctua pronuba. The index of detectability (d′) was calculated either from ROC curves or from a procedure equivalent to a two-alternatives forced-choice paradigm of psychophysics. Stimuli of six different durations (1–40 ms) were used. The detectability increased exponentially with intensity for all signals and with the rate of increase independent of duration. This allowed for an evaluation of the influence of stimulus duration on detectability (duration/intensity trade-off). A model of statistical threshold improvement (the “multiple looks” model) could be applied and the influence of statistics on thresholds could be separated from the influence of intensity integration. For stimulus durations significantly shorter than the time constant of the receptor (3.4 ms for N. pronuba), intensity integration was the main factor determining thresholds and thus an energy detector model was applicable to the data. For durations significantly longer than the time constant, the multiple look model alone could account for changes in thresholds with duration. For durations in-between, a mixture of both models was applicable, making specific predictions difficult.

Detection of short pure-tone stimuli in the noctuid ear: what are temporal integration and integration time all about?

Temporal integration in the A1 acoustic receptor cell of noctuid moths (Lepidoptera: Noctuidae) was studied. This was done by recording from the auditory nerve of Spodoptera littoralis and Noctua pronuba while stimulating with short-duration tone pulses. Consistent with previous experiments of the same kind, a decrease in threshold was observed with increasing stimulus duration. These threshold improvements, however, were larger than expected from an energy detector model of the receptor based on previous experiments with double clicks. This difference was analysed and could be attributed to a bias introduced by the choice of threshold criterion. If a fixed number of spikes elicited per stimulation is used as criterion, this will tend to lower the measured thresholds for long durations because for long stimuli, more time is available for accumulation of the spikes needed to exceed the criterion. It appears that temporal integration in the noctuid ear can be characterised by different time constants. One, termed the intrinsic time constant, is measured in the double-click experiments and provides information about the temporal integration and resolution within the receptor cell. Behavioural time constants, on the other hand, characterise the temporal integration reflected in the behaviour of the animals.

Energy detection and temporal integration in the noctuid A1 auditory receptor

The temporal integration of the A1 auditory receptor of two species of noctuid moths (Lepidoptera, Noctuidae) was investigated. Tympanal nerve spikes were recorded while stimulating the ear with broad band clicks. Thresholds were measured for single clicks, pairs of clicks with a separation of 1–20 ms, and trains of up to 8 clicks at separations of 1–2 ms. The average threshold for single clicks was 52.9 dB peSPL (SD 1.7 dB, n = 40) for Noctua pronuba and 50.1 dB peSPL (SD 4.0 dB, n = 27) for Spodoptera littoralis. The thresholds for double clicks with a 1 ms separation were lower than the thresholds for single clicks. The difference decreased as the separation between the clicks was increased. The results were fully consistent with an energy detector model (a leaky integrator with an exponential decay) with a time constant of about 4 ms. The results are compared to previously published results with pure tone intensity/duration trading. A common underlying mechanism is suggested, based on the passive electric properties of the receptor cell membrane. It is suggested, that the time constant revealed in the present study characterizes auditory receptors in general, and is related to the short time constants in vertebrate audition.

Stimulus fluctuations in auditory intensity discrimination.

A basic prediction of Green’s [J. Acoust. Soc. Am. 32, 121–131 (1960)] classical energy‐detection theory for Gaussian signals is a variance measure of stimulus fluctuation that decreases monotonically with the signal’s duration‐bandwidth product (TW). Experiments on intensity discrimination of narrow‐band Gaussian noise provide the most direct support of this prediction for TW<∼16, but indicate a need for another source of fluctuation for larger TW which could reflect internal noise [deBoer, J. Acoust. Soc. Am. 40, 552–560 (1966)]. An alternative solution is proposed based on detection of the largest waveform peak within the analysis window (≥T). Investigation of this detector for narrow‐band Gaussian noise shows that the variance (in dB) of the peak fluctuations is the sum of the variances of the classical energy fluctuation and of a waveform fluctuation due to random phases. For TW<20 the energy fluctuation dominates, while the waveform fluctuation dominates for larger TW. Predictions of the classical energy detection model with an internal noise of 1 dB are essentially indistinguishable from the peak detector model for intensity discrimination thresholds of narrow‐band Gaussian noise; however, peak detection explains a wider range of experiments [Goldstein, J. Acoust. Soc. Am. 98, 2907(A) (1995)].

Detecting signals of unexpected or uncertain durations.

Expectation of signal duration influences the signal detectability. This is demonstrated in two experiments in which percent correct was measured for both tonal and noise signals whose durations were either unexpected or uncertain. In both experiments, the signal at each duration was set to have a d' of about 1.5 when that duration was presented alone and expected. When the six subjects were led to expect a short- or a long-duration signal using the probe-signal method, the detectability of signals decreased to near chance as the signal duration deviated from the expected value (experiment 1). When the subjects were led to expect a range of durations, the detectability was only slightly worse than when each signal was presented alone (experiment 2). Those results suggest that listeners adjust their temporal-integration intervals according to the demand of the specific task. Finally, the results obtained with the noise signal were analyzed using the multiple-look model and a modified energy-detector model. Assuming that the integration interval is matched to the expected signal duration, both models predict the detection of signals having unexpected durations reasonably well. Both models, however, fail to predict the small effect of duration uncertainty.

Increment detection of bandlimited noises in the chinchilla

A positive reinforcement, adaptive tracking procedure was used to study the intensity discrimination abilities of six chinchillas to noise signals. Increment detection thresholds were obtained using a two-down, one-up tracking rule. The effect of overall noise masker level and the effect of noise bandwidth on increment detection thresholds were studied. The continuous noise masker and the signal increment had equal bandwidths. Increment detection thresholds are independent of overall level for wideband noise; the asymtotic DL for wideband noise is 1.334 dB. In addition, increment detection thresholds decrease as the bandwidth of the noise increases. The observed slope of the bandwidth function for the chinchilla is independent of overall level and is around − 2.8 dB/decade. The slope of the bandwidth function obtained for the chinchilla is similar to values reported for human subjects under similar conditions, but is less than the slope predicted by the ideal energy detector model.