White Noise Techniques Research Articles

Multi-Patch Time Series Transformer for Robust Bearing Fault Detection with Varying Noise

In time-series studies involving bearing sensor data, Gaussian noise and white noise techniques are commonly employed to evaluate model robustness. However, these conventional noise techniques are limited in their applicability to real-world industrial environments. This paper proposes three novel noise techniques—electrical interference noise, harmonic noise, and random shock noise—that more accurately reflect the complex noise encountered in industrial settings. Additionally, a new deep learning model, MultiPatchTST, is introduced, demonstrating robust performance under various noise conditions. Experimental results reveal that Gaussian noise has minimal impact on model performance, whereas the proposed noise techniques significantly affect performance, providing a more realistic evaluation of noise robustness. The proposed MultiPatchTST model achieves superior performance across all metrics in the presence of all four noise types, confirming its robustness and reliability.

The impulse response of optic flow-sensitive descending neurons to roll m-sequences.

ABSTRACTWhen animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow-sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensorimotor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. Therefore, here we used m-sequences to quantify the impulse responses of optic flow-sensitive descending neurons in male Eristalis tenax hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5–18.0 ms. This is similar to the impulse response time to peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift.

Enhanced Indonesian Ethnic Speaker Recognition using Data Augmentation Deep Neural Network

Speaker Recognition is a challenging topic in Speech Processing research area. The various models proposed have succeeded in achieving a fairly high level of accuracy in this research. However, the level of Speaker Recognition accuracy is not yet maximized because the small dataset is a problem that is still being faced at this time, causing overfitting and biased data samples. This work proposes a Data Augmentation strategy using Adding White Noise techniques, Pitch Shifting, and Time Stretching, which are processed using a Deep Neural Network to produce a new model in speaker recognition as an approach called as DA-DNN7L. The Data Augmentation approach is used as a solution to increase the limited data quantity of Indonesian ethnic speakers, while the seven layer DNN is an architecture that provides the best accuracy performance compared to other multilayer approach models, besides that the 7 layer approach used in several other studies achieves a high degree of accuracy. Research that has been carried out using the best performance seven-layer Deep Neural Network Data Augmentation strategy resulted in an accuracy rate of 99.76% and a loss of 0.05 in the 70%:30% split ratio and the addition of 400 augmentation data. After seeing the performance of this model, it can be concluded that Data Augmentation Deep Neural Network can improve the speaker's recognition performance using the Indonesian ethnic dataset.

Noise Level Estimation for Digital Images Using Local Statistics and Its Applications to Noise Removal

In this paper, an automatic estimation of additive white Gaussian noise technique is proposed. This technique is built according to the local statistics of Gaussian noise. In the field of digital signal processing, estimation of the noise is considered as pivotal process that many signal processing tasks relies on. The main aim of this paper is to design a patch-based estimation technique in order to estimate the noise level in natural images and use it in blind image removal technique. The estimation processes is utilized selected patches which is most contaminated sub-pixels in the tested images sing principal component analysis (PCA). The performance of the suggested noise level estimation technique is shown its superior to state of the art noise estimation and noise removal algorithms, the proposed algorithm produces the best performance in most cases compared with the investigated techniques in terms of PSNR, IQI and the visual perception.

Spatio-temporal dynamics of impulse responses to figure motion in optic flow neurons.

White noise techniques have been used widely to investigate sensory systems in both vertebrates and invertebrates. White noise stimuli are powerful in their ability to rapidly generate data that help the experimenter decipher the spatio-temporal dynamics of neural and behavioral responses. One type of white noise stimuli, maximal length shift register sequences (m-sequences), have recently become particularly popular for extracting response kernels in insect motion vision. We here use such m-sequences to extract the impulse responses to figure motion in hoverfly lobula plate tangential cells (LPTCs). Figure motion is behaviorally important and many visually guided animals orient towards salient features in the surround. We show that LPTCs respond robustly to figure motion in the receptive field. The impulse response is scaled down in amplitude when the figure size is reduced, but its time course remains unaltered. However, a low contrast stimulus generates a slower response with a significantly longer time-to-peak and half-width. Impulse responses in females have a slower time-to-peak than males, but are otherwise similar. Finally we show that the shapes of the impulse response to a figure and a widefield stimulus are very similar, suggesting that the figure response could be coded by the same input as the widefield response.

Bionic Baroreceptor Corrects Postural Hypotension in Rats With Impaired Baroreceptor

Impairment of the arterial baroreflex causes orthostatic hypotension. Arterial baroreceptor sensitivity degrades with age. Thus, an impaired baroreceptor plays a pivotal role in orthostatic hypotension in most elderly patients. There is no effective treatment for orthostatic hypotension. The aims of this investigation were to develop a bionic baroreceptor (BBR) and to verify whether it corrects postural hypotension. The BBR consists of a pressure sensor, a regulator, and a neurostimulator. In 35 Sprague-Dawley rats, we vascularly and neurally isolated the baroreceptor regions and attached electrodes to the aortic depressor nerve for stimulation. To mimic impaired baroreceptors, we maintained intracarotid sinus pressure at 60 mm Hg during activation of the BBR. Native baroreflex was reproduced by matching intracarotid sinus pressure to the instantaneous pulsatile aortic pressure. The encoding rule for translating intracarotid sinus pressure into stimulation of the aortic depressor nerve was identified by a white noise technique and applied to the regulator. The open-loop arterial pressure response to intracarotid sinus pressure (n=7) and upright tilt-induced changes in arterial pressure (n=7) were compared between native baroreceptor and BBR conditions. The intracarotid sinus pressure-arterial pressure relationships were comparable. Compared with the absence of baroreflex, the BBR corrected tilt-induced hypotension as effectively as under native baroreceptor conditions (native, -39±5 mm Hg; BBR, -41±5 mm Hg; absence, -63±5 mm Hg; P<0.05). The BBR restores the pressure buffering function. Although this research demonstrated feasibility of the BBR, further research is needed to verify its long-term effect and safety in larger animal models and humans.

Applicability of White-Noise Techniques to Analyzing Motion Responses

Motion processing in visual neurons is often understood in terms of how they integrate light stimuli in space and time. These integrative properties, known as the spatiotemporal receptive fields (STRFs), are sometimes obtained using white-noise techniques where a continuous random contrast sequence is delivered to each spatial location within the cell's field of view. In contrast, motion stimuli such as moving bars are usually presented intermittently. Here we compare the STRF prediction of a neuron's response to a moving bar with the measured response in second-order interneurons (L-neurons) of dragonfly ocelli (simple eyes). These low-latency neurons transmit sudden changes in intensity and motion information to mediate flight and gaze stabilization reflexes. A white-noise analysis is made of the responses of L-neurons to random bar stimuli delivered either every frame (densely) or intermittently (sparsely) with a temporal sequence matched to the bar motion stimulus. Linear STRFs estimated using the sparse stimulus were significantly better at predicting the responses to moving bars than the STRFs estimated using a traditional dense white-noise stimulus, even when second-order nonlinear terms were added. Our results strongly suggest that visual adaptation significantly modifies the linear STRF properties of L-neurons in dragonfly ocelli during dense white-noise stimulation. We discuss the ability to predict the responses of visual neurons to arbitrary stimuli based on white-noise analysis. We also discuss the likely functional advantages that adaptive receptive field structures provide for stabilizing attitude during hover and forward flight in dragonflies.

Using White Noise to Probe Actomyosin Cycling Kinetics During Shortening and Lengthening in Drosophila Flight Muscle Fibers

Our laboratory routinely measures demembranated muscle fiber mechanics using small amplitude sinusoidal length perturbation analysis and estimates kinetics of actomyosin cycling and myosin attachment time. We have developed a complementary measurement technique using small, random changes in muscle length (white-noise length stimuli) that simultaneously cover a broad frequency spectrum, comparable with the sinusoidal length perturbations. We find the white-noise technique provides a description of the viscoelastic properties that is consistent with sinusoidal analysis measurements, rapidly capturing much of the physiological behavior associated with contracting muscle fibers. The white-noise technique samples a vast range of system behavior in a fraction of the time required to complete sinusoidal analysis, and does not require the linear response underlying sinusoidal analysis methods. Thus, we combined the white-noise stimuli with a linear shortening and lengthening transients to probe cross-bridge cycling behavior during these periods of varied load. Preliminary measurements using demembranated dorsal longitudinal flight muscle fibers from Drosophila melanogaster indicate faster cross-bridge cycling kinetics during lengthening and slower cycling during shortening, compared to isometric contraction. During isometric contraction we estimate a myosin attachment time of 5.0 ms, and 4.6 versus 5.5 ms during the lengthening and shortening transients, respectively. These initial applications of the white-noise system analysis technique show promise for future studies probing molecular processes that underlie complicated length transients associated with normal muscle contraction.

Explicit Representation of Strong Solutions of SDEs Driven by Infinite-Dimensional Lévy Processes

We develop a white noise framework for Levy processes on Hilbert spaces. As the main result of this paper, we then employ these white noise techniques to explicitly represent strong solutions of stochastic differential equations driven by a Hilbert-space-valued Levy process.

Numerical simulations of generalized Langevin equations with deeply asymptotic parameters

A unified algorithm for solving Langevin equations with deeply asymptotic parameters is proposed and tested. The method consists of identifying solvable linear friction and implementing the force evaluations by use of the Runge-Kutta method. We apply the present scheme to the periodic motion of an overdamped particle subjected to a multiplicative white noise. The accurate calculations for the temporal velocity of the particle and its correlation function can be realized by introducing an inertial term. It is shown that the fluctuation around the steady quantity increases with decreasing time step in the overdamped white-noise algorithm, however, a massive white-noise technique greatly reduces this spurious drift, and the result can converge to the correct value if the added inertia approaches zero. The other application is the simulation of generalized Langevin equation with an exponential memory friction, this allows us to treat a weak non-Markovian process.

A generalization of the Itô formula

The classical Itô formula is generalized to some anticipating processes. The processes we consider are in a Sobolev space which is a subset of the space of square integrable functions over a white noise space. The proof of the result uses white noise techniques.

A simple white noise analysis of neuronal light responses

A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes classical linear systems analysis. A theoretical justification of the technique is presented that relies only on elementary linear algebra and statistics. Implementation is described with examples. The technique and the underlying model of neural responses are validated using recordings from retinal ganglion cells, and in principle are applicable to other neurons. Advantages and disadvantages of the technique relative to classical approaches are discussed.

Alternative Simulating Technique for Periodic Motion in the Presence of Multiplicative White Noise

An effective approach for simulating the periodic motion of an overdamped particle subjected to a multiplicative white-noise source is described. The accurate calculations for the velocity of the particle and its correlation function can be realized by introducing an inertial term. The results show that fluctuation around a time-averaged quantity increases with decreasing time step in the overdamped white-noise algorithm, however, a massive white-noise technique greatly reduces this spurious drift. In particular, the present algorithm converges on the correct values of the calculated quantities, while the mass of the particle approaches to zero.

Photoreceptor performance and the co-ordination of achromatic and chromatic inputs in the fly visual system

White noise techniques are used to compare the two photoreceptor sub-types in blowfly retina, the short visual fibres (R1-6) that code achromatic contrast, and the long visual fibres (R7 and R8) that together code wavelength distribution and polarisation plane. Measurements of signal and noise spectra and contrast gain, taken across a broad intensity range, permit a detailed comparison of coding efficiency under natural conditions of illumination. As a function of excitation (effective photons per photoreceptor per second; h upsilon/rec per s), adaptive changes in the long and short visual fibres are similar, suggesting that post-rhodopsin their phototransduction cascades are identical. Under identical natural daylight conditions (photons per cm2 per second; h upsilon/cm2 per s) short visual fibres catch more photons, thus operating with a higher signal to noise ratio and faster response, to consistently outperform the long visual fibres. Long visual fibres compensate for their poor quantum catch by having a higher absolute gain (mV/h upsilon) which at low light intensities enables them to achieve a level of contrast gain (mV/unit contrast) similar to the short visual fibres. Differences in signal to noise ratios are related to known differences in photoreceptor structure and synaptic frequency among visual interneurons. The principles of matching sensitivity and synapse number to quantum catch described here could explain analogous differences between chromatic and achromatic pathways in mammalian and amphibian retinas.

Neuronal uptake affects dynamic characteristics of heart rate response to sympathetic stimulation.

Recently, studies in our laboratory involving the use of a Gaussian white noise technique demonstrated that the transfer function from sympathetic stimulation frequency to heart rate (HR) response showed dynamic characteristics of a second-order low-pass filter. However, determinants for the characteristics remain to be established. We examined the effect of an increase in mean sympathetic stimulation frequency and that of a blockade of the neuronal uptake mechanism on the transfer function in anesthetized rabbits. We found that increasing mean sympathetic stimulation frequency from 1 to 4 Hz significantly (P < 0.01) decreased the dynamic gain of the transfer function without affecting other parameters, such as the natural frequency, lag time, or damping coefficient. In contrast, the administration of desipramine (0.3 mg/kg iv), a neuronal uptake blocking agent, significantly (P < 0.01) decreased both the dynamic gain and the natural frequency and prolonged the lag time. These results suggest that the removal rate of norepinephrine at the neuroeffector junction, rather than the amount of available norepinephrine, plays an important role in determining the low-pass filter characteristics of the HR response to sympathetic stimulation.

Cholinesterase affects dynamic transduction properties from vagal stimulation to heart rate.

Recent investigations in our laboratory using a Gaussian white noise technique showed that the transfer function representing the dynamic properties of transduction from vagus nerve activity to heart rate had characteristics of a first-order low-pass filter. However, the physiological determinants of those characteristics remain to be elucidated. In this study, we stimulated the vagus nerve according to a Gaussian white noise pattern to estimate the transfer function from vagal stimulation to the heart rate response in anesthetized rabbits and examined how changes in acetylcholine kinetics affected the transfer function. We found that although increases in the mean frequency of vagal stimulation from 5 to 10 Hz did not change the characteristics of the transfer function, administration of neostigmine (30 microg . kg-1 . h-1 iv), a cholinesterase inhibitor, increased the dynamic gain from 8.19 +/- 3.66 to 11.7 +/- 4.88 beats . min-1 . Hz-1 (P < 0.05), decreased the corner frequency from 0.12 +/- 0.05 to 0.04 +/- 0.01 Hz (P < 0.01), and increased the lag time from 0.17 +/- 0.12 to 0.27 +/- 0.08 s (P < 0.05). These results suggest that the rate of acetylcholine degradation at the neuroeffector junction, rather than the amount of available acetylcholine, plays a key role in determining the dynamic properties of transduction from vagus nerve activity to heart rate.

Dynamic transduction properties of in situ baroreceptors of rabbit aortic depressor nerve.

We developed a new method for isolating in situ baroreceptor regions of the rabbit aortic depressor nerve (ADN) and estimated the transfer function from pressure to afferent nerve activity in the frequency range of 0.01-5 Hz by a white noise technique. Complete isolation of the baroreceptor area of the right ADN was made in situ by ligation of the innominate artery and the right subclavian and common carotid arteries. We altered the pressure in the isolated baroreceptor area according to a binary quasi-white noise between 80 and 100 mmHg in 12 urethan-anesthetized rabbits. The gain increased two to three times as the frequency of pressure perturbation increased from 0.01 to 2 Hz and then decreased at higher frequencies. The phase slightly led below 0.2 Hz. The squared coherence value was > 0.8 in the frequency range of 0.01-4 Hz. The step responses estimated from the transfer function were indistinguishable from those actually observed. We conclude that the baroreceptor transduction of the ADN is governed by linear dynamics under the physiological operating pressure range.

Investigation of transition to turbulence using white-noise excitation and local analysis techniques

Weak free-stream turbulence excites modulated Tollmien–Schlichting (T–S) waves in a laminar boundary layer that grow in magnitude with downstream distance and ultimately lead to the formation of turbulent spots and then fully turbulent flow. Hot-wire experiments have indicated that the development of localized large-amplitude ‘events’ in the velocity records are the essential precursor to the eventual formation of turbulent spots in the flow field. Traditional global Fourier techniques are unable to resolve the localized nature of these events and hence provide little useful information concerning the physical processes responsible for this breakdown process.This investigation used sequences of computer-generated deterministic white noise to excite a laminar boundary layer via a loudspeaker embedded in a flat-plate model. This form of excitation generated the modulated disturbance waves of interest a short distance downstream from the source in a repeatable and deterministic manner. Further downstream the pattern of flow breakdown and subsequent generation of turbulent spots was similar to that observed in naturally excited situations. By repeatedly exciting the boundary layer with a single white-noise sequence it was possible to examine the highly nonlinear stages of ‘event’ development and breakdown with a single hot-wire probe.Two local analysis techniques, the wavelet transform (WT) and singular spectrum analysis (SSA), were used in conjunction with the white-noise excitation technique to examine the highly nonlinear flow mechanisms responsible for the localized formation of events that lead to the eventual breakdown to turbulence.

A subspace reverse-correlation technique for the study of visual neurons.

A new discrete-time reverse-correlation scheme for the study of visual neurons is proposed. The visual stimulus is generated by drawing with uniform probability, at each refresh time, an image from a finite set S of orthonormal images. We show that if the neuron can be modeled as a spatiotemporal linear filter followed by a static nonlinearity, the cross-correlation between the input image sequence and the cell's spike train output gives the projection of the receptive field onto the subspace spanned by S. The technique has been applied to the analysis of simple cells in the primary visual cortex of cats and macaque monkeys. Experimental results are presented where S spans a subspace of spatially low-pass signals. Advantages of the proposed scheme over standard white-noise techniques include improved signal to noise ratios, increased spatial resolution, and the possibility to restrict the study to particular subspaces of interest.

Bidirectional augmentation of heart rate regulation by autonomic nervous system in rabbits.

Although the characteristics of the static interaction between the sympathetic and parasympathetic nervous systems in regulating heart rate (HR) have been well established, how the dynamic interaction modulates the HR response remains unknown. We therefore investigated dynamic interaction by estimating the transfer function from nerve stimulation to HR using a band-limited Gaussian white-noise technique. The transfer function relating dynamic sympathetic stimulation to HR had characteristics of a second-order low-pass filter. Simultaneous tonic vagal stimulation at 5 and 10 Hz increased gain of the transfer function by 55.0 +/- 40.1 and 80.7 +/- 50.5%, respectively (P < 0.05). The transfer function from dynamic vagal stimulation to HR had characteristics of a first-order low-pass filter. Simultaneous tonic sympathetic stimulation at 5 and 10 Hz increased the gain by 18.2 +/- 17.9 and 24.1 +/- 18.0%, respectively (P < 0.05). Thus interaction augmented dynamic gain bidirectionally, even though it affected mean HR antagonistically. By virtue of this interaction, the autonomic nervous system appears to extend its dynamic range of operation.