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Articoli di riviste sul tema "White noise"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

Tellis, Ashley. "White Noise." Transforming Anthropology 13, no. 2 (2005): 148–49. http://dx.doi.org/10.1525/tran.2005.13.2.148.

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2

George David Clark. "WHITE NOISE." Antioch Review 72, no. 1 (2014): 149. http://dx.doi.org/10.7723/antiochreview.72.1.0149.

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3

Lööw, Heléne. "White Noise." Index on Censorship 27, no. 6 (1998): 153–55. http://dx.doi.org/10.1080/03064229808536482.

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4

morton, mark. "White Noise." Gastronomica 9, no. 3 (2009): 6–7. http://dx.doi.org/10.1525/gfc.2009.9.3.6.

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5

Banerjee, Mousumi. "White Noise." JAMA Oncology 4, no. 12 (2018): 1793. http://dx.doi.org/10.1001/jamaoncol.2018.4644.

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6

Nobes, Karen, and Susan Kerrigan. "White noise." Alphaville: Journal of Film and Screen Media, no. 24 (December 20, 2022): 79–96. http://dx.doi.org/10.33178/alpha.24.05.

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Abstract (sommario):

First Nations content on commercial Australian television drama is rare and First Nations content makers rarely produce the content we see. Despite a lack of presence on commercial drama platforms there has been, and continues to be, a rich array of First Nations content on Australian public broadcast networks. Content analysis by Screen Australia, the Federal Government agency charged with supporting Australian screen development, production and promotion, aggregates information across the commercial and non-commercial (public broadcasting) platforms which dilutes the non-commercial output. T

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7

CHUNG, DONG MYUNG, UN CIG JI, and NOBUAKI OBATA. "QUANTUM STOCHASTIC ANALYSIS VIA WHITE NOISE OPERATORS IN WEIGHTED FOCK SPACE." Reviews in Mathematical Physics 14, no. 03 (2002): 241–72. http://dx.doi.org/10.1142/s0129055x0200117x.

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White noise theory allows to formulate quantum white noises explicitly as elemental quantum stochastic processes. A traditional quantum stochastic differential equation of Itô type is brought into a normal-ordered white noise differential equation driven by lower powers of quantum white noises. The class of normal-ordered white noise differential equations covers quantum stochastic differential equations with highly singular noises such as higher powers or higher order derivatives of quantum white noises, which are far beyond the traditional Itô theory. For a general normal-ordered white noise

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8

Huang, Zhiyuan. "Quantum white noises—White noise approach to quantum stochastic calculus." Nagoya Mathematical Journal 129 (March 1993): 23–42. http://dx.doi.org/10.1017/s002776300000430x.

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Let H = L2 (R) be the Hilbert space of all complex-valued square integrable functions defined on R, Ф = Γ(H) be the Boson Fock space over H. For each h ∈ H, denote by ε(h) the corresponding exponential vector:in particular ε(0) is the Fock vacuum.

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9

Leggat, Graham. "Making White Noise." Afterimage 18, no. 6 (1991): 3–4. http://dx.doi.org/10.1525/aft.1991.18.6.3.

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10

Carter, Steven. "DeLillo's WHITE NOISE." Explicator 58, no. 2 (2000): 115–16. http://dx.doi.org/10.1080/00144940009597033.

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11

&NA;. "White Noise [Excerpt]." Academic Medicine 89, no. 9 (2014): 1228. http://dx.doi.org/10.1097/acm.0000000000000392.

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12

Grigoriu, Mircea. "White Noise Processes." Journal of Engineering Mechanics 113, no. 5 (1987): 757–65. http://dx.doi.org/10.1061/(asce)0733-9399(1987)113:5(757).

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13

Bakalis, Evangelos, Francesca Lugli, and Francesco Zerbetto. "Daughter Coloured Noises: The Legacy of Their Mother White Noises Drawn from Different Probability Distributions." Fractal and Fractional 7, no. 8 (2023): 600. http://dx.doi.org/10.3390/fractalfract7080600.

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Abstract (sommario):

White noise is fundamentally linked to many processes; it has a flat power spectral density and a delta-correlated autocorrelation. Operators acting on white noise can result in coloured noise, whether they operate in the time domain, like fractional calculus, or in the frequency domain, like spectral processing. We investigate whether any of the white noise properties remain in the coloured noises produced by the action of an operator. For a coloured noise, which drives a physical system, we provide evidence to pinpoint the mother process from which it came. We demonstrate the existence of tw

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14

Selvaraj, Poovarasan, and E. Chandra. "A variant of SWEMDH technique based on variational mode decomposition for speech enhancement." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 3 (2021): 299–308. http://dx.doi.org/10.3233/kes-210072.

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In Speech Enhancement (SE) techniques, the major challenging task is to suppress non-stationary noises including white noise in real-time application scenarios. Many techniques have been developed for enhancing the vocal signals; however, those were not effective for suppressing non-stationary noises very well. Also, those have high time and resource consumption. As a result, Sliding Window Empirical Mode Decomposition and Hurst (SWEMDH)-based SE method where the speech signal was decomposed into Intrinsic Mode Functions (IMFs) based on the sliding window and the noise factor in each IMF was c

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15

Park, Hyun-Sang. "Gaussian Noise Estimation Using White Noise Test." Journal of Korean Institute of Information Technology 16, no. 4 (2018): 51–56. http://dx.doi.org/10.14801/jkiit.2018.16.4.51.

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16

Ji, Un Cig. "Evolution systems and continuity equations for white noise functionals." Journal of Mathematical Physics 63, no. 10 (2022): 101504. http://dx.doi.org/10.1063/5.0073993.

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In this paper, by applying the quantum decomposition of white noise functionals, the continuity equations for white noise functionals are reformulated as time inhomogeneous white noise differential equations. We establish a systematic study of the evolution systems whose infinitesimal generators are quadratic quantum white noises and then, as an application, we study the continuity equations for white noise functionals of which the coefficient has up to the first chaos (Gaussian process). The restriction for the coefficient is comparable (not necessarily equivalent) to the integrability condit

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17

Starosta, William J. "Afrocentric Voice, White Noise." Contemporary Psychology 46, no. 3 (2001): 242–44. http://dx.doi.org/10.1037/002478.

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18

Barhoumi, Abdessatar, Habib Ouerdiane, and Anis Riahi. "Pascal white noise calculus." Stochastics 81, no. 3-4 (2009): 323–43. http://dx.doi.org/10.1080/17442500902919603.

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19

REDFERN, MYLAN. "COMPLEX WHITE NOISE ANALYSIS." Infinite Dimensional Analysis, Quantum Probability and Related Topics 04, no. 03 (2001): 347–75. http://dx.doi.org/10.1142/s0219025701000541.

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This paper describes a new space, [Formula: see text], of complex Wiener distributions for the analysis of multi-parameter generalized stochastic processes [Formula: see text]. For a certain class of functions [Formula: see text] and complex Wiener integrals Φ1, …, Φm, F(Φ1, …, Φm) is defined as an element of [Formula: see text] and its Fock space decomposition determined.

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20

Accardi, Luigi, and Wided Ayed. "Free white noise flows." Infinite Dimensional Analysis, Quantum Probability and Related Topics 20, no. 03 (2017): 1750014. http://dx.doi.org/10.1142/s021902571750014x.

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Abstract (sommario):

We extend to free white noise Heisenberg equations the proof of the equivalence between (non-Hamiltonian) stochastic differential equations and Hamiltonian white noise equations. This gives in particular, the microscopic structure of the maps defining free white noise stochastic flows in terms of the free white noise derivations defining them.

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21

Accardi, L., W. Ayed, and H. Ouerdiane. "Module white noise calculus." Random Operators and Stochastic Equations 15, no. 4 (2007): 353–86. http://dx.doi.org/10.1515/rose.2007.022.

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22

Allen, William S. "WHITE NOISE, ÉCRITURE BLANCHE." Angelaki 23, no. 3 (2018): 28–41. http://dx.doi.org/10.1080/0969725x.2018.1473925.

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23

Frank, David W., Ryan B. Yee, and John Polich. "P3a from white noise." International Journal of Psychophysiology 85, no. 2 (2012): 236–41. http://dx.doi.org/10.1016/j.ijpsycho.2012.04.005.

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24

Quastel, Jeremy, and Benedek Valkó. "KdV Preserves White Noise." Communications in Mathematical Physics 277, no. 3 (2007): 707–14. http://dx.doi.org/10.1007/s00220-007-0372-6.

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25

Benson, Josef. "Hypermedicalization in White Noise." Journal of Medical Humanities 36, no. 3 (2014): 199–215. http://dx.doi.org/10.1007/s10912-014-9271-y.

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26

Crauel, H. "White noise eliminates instability." Archiv der Mathematik 75, no. 6 (2000): 472–80. http://dx.doi.org/10.1007/s000130050532.

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27

Ji, Un Cig, Mi Ra Lee, and Peng Cheng Ma. "Generalized Mehler Semigroup on White Noise Functionals and White Noise Evolution Equations." Mathematics 8, no. 6 (2020): 1025. http://dx.doi.org/10.3390/math8061025.

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In this paper, we study a representation of generalized Mehler semigroup in terms of Fourier–Gauss transforms on white noise functionals and then we have an explicit form of the infinitesimal generator of the generalized Mehler semigroup in terms of the conservation operator and the generalized Gross Laplacian. Then we investigate a characterization of the unitarity of the generalized Mehler semigroup. As an application, we study an evolution equation for white noise distributions with n-th time-derivative of white noise as an additive singular noise.

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28

Wang, Xin, Shu-Li Sun, Kai-Hui Ding, and Jing-Yan Xue. "Weighted Measurement Fusion White Noise Deconvolution Filter with Correlated Noise for Multisensor Stochastic Systems." Mathematical Problems in Engineering 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/257619.

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For the multisensor linear discrete time-invariant stochastic control systems with different measurement matrices and correlated noises, the centralized measurement fusion white noise estimators are presented by the linear minimum variance criterion under the condition that noise input matrix is full column rank. They have the expensive computing burden due to the high-dimension extended measurement matrix. To reduce the computing burden, the weighted measurement fusion white noise estimators are presented. It is proved that weighted measurement fusion white noise estimators have the same accu

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29

Kia, Behnam, Sarvenaz Kia, John F. Lindner, Sudeshna Sinha, and William L. Ditto. "Coupling Reduces Noise: Applying Dynamical Coupling to Reduce Local White Additive Noise." International Journal of Bifurcation and Chaos 25, no. 03 (2015): 1550040. http://dx.doi.org/10.1142/s0218127415500406.

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Abstract (sommario):

We demonstrate how coupling nonlinear dynamical systems can reduce the effects of noise. For simplicity we investigate noisy coupled map lattices and assume noise is white and additive. Noise from different lattice nodes can diffuse across the lattice and lower the noise level of individual nodes. We develop a theoretical model that explains this observed noise evolution and show how the coupled dynamics can naturally function as an averaging filter. Our numerical simulations are in excellent agreement with the model predictions.

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30

Cao, Jiyuan, Yanwen Wang, Weixiong Zhu, and Yihe Zhang. "A Noise Reduction Algorithm for White Noise and Periodic Narrowband Interference Noise in Partial Discharge Signals." Applied Sciences 15, no. 4 (2025): 1760. https://doi.org/10.3390/app15041760.

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Partial discharge (PD) detection plays an important role in online condition monitoring of electrical equipment and power cables. However, the noise of PD measurement will significantly reduce the performance of the detection algorithm. In this paper, we focus on the study of a PD noise reduction algorithm based on improved singular value decomposition (SVD) and multivariate variational mode decomposition (MVMD) for white Gaussian noise (WGN) and periodic narrowband interference signal noise. The specific noise reduction algorithm is divided into three noise reduction processes: The first nois

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31

Chung, Dong Myung, Un Cig Ji, and Nobuaki Obata. "Higher Powers of Quantum White Noises in Terms of Integral Kernel Operators." Infinite Dimensional Analysis, Quantum Probability and Related Topics 01, no. 04 (1998): 533–59. http://dx.doi.org/10.1142/s0219025798000296.

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Abstract (sommario):

A rigorous mathematical formulation of higher powers of quantum white noises is given on the basis of the most recent theory of white noise distributions due to Cochran, Kuo and Sengupta. The renormalized quantum Itô formula due to Accardi, Lu and Volovich is derived from the renormalized product formula based on integral kernel operators on white noise functions. During the discussion, the analytic characterization of operator symbols and the expansion theorem for a white noise operator in terms of integral kernel operators are established.

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32

Alokaily, Ahmad O., Abdulaziz F. Alqabbani, Adham Aleid, and Khalid Alhussaini. "Toward Accessible Hearing Care: The Development of a Versatile Arabic Word-in-Noise Screening Tool: A Pilot Study." Applied Sciences 12, no. 23 (2022): 12459. http://dx.doi.org/10.3390/app122312459.

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Abstract (sommario):

Speech-in-noise tests are used to assess the ability of the human auditory system to perceive speech in a noisy environment. Early diagnosis of hearing deficits helps health professionals to plan for the most appropriate management. However, hospitals and auditory clinics have a shortage of reliable Arabic versions of speech-in-noise tests. Additionally, access to specialized healthcare facilities is associated with socioeconomic status. Hence, individuals with compromised socioeconomic status do not have proper access to healthcare. Thus, In the current study, a mobile and cost-effective Arab

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33

CHEN, J., X. X. YI, H. S. SONG, and L. ZHOU. "NOISE INDUCED ENTANGLEMENT." International Journal of Quantum Information 03, no. 02 (2005): 425–33. http://dx.doi.org/10.1142/s0219749905001031.

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We show that two two-level atoms coupled simultaneously with a third dissipated atom would end up with entangled states. The dissipation of the third atom is supposed to come from its coupling to noises with adjustable intensity. Two kinds of noise, white noise and squeezing white noise, are identified to possess the ability to help preparation of entanglement. We confirm that the entanglement is maximized for intermediate values of the noise intensity with all atoms in the ground state, while it is a monotonic function of the spontaneous rates.

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34

Li, Yongsong, Zhengzhou Li, Kai Wei, Weiqi Xiong, Jiangpeng Yu, and Bo Qi. "Noise Estimation for Image Sensor Based on Local Entropy and Median Absolute Deviation." Sensors 19, no. 2 (2019): 339. http://dx.doi.org/10.3390/s19020339.

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Abstract (sommario):

Noise estimation for image sensor is a key technique in many image pre-processing applications such as blind de-noising. The existing noise estimation methods for additive white Gaussian noise (AWGN) and Poisson-Gaussian noise (PGN) may underestimate or overestimate the noise level in the situation of a heavy textured scene image. To cope with this problem, a novel homogenous block-based noise estimation method is proposed to calculate these noises in this paper. Initially, the noisy image is transformed into the map of local gray statistic entropy (LGSE), and the weakly textured image blocks

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35

ACCARDI, LUIGI, and MICHAEL SKEIDE. "ON THE RELATION OF THE SQUARE OF WHITE NOISE AND THE FINITE DIFFERENCE ALGEBRA." Infinite Dimensional Analysis, Quantum Probability and Related Topics 03, no. 01 (2000): 185–89. http://dx.doi.org/10.1142/s021902570000011x.

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The algebra of square of white noise1 contains a subalgebra generated by elements fulfilling the relations of Feinsilver's finite difference algebra.6 Moreover, Boukas' representation space3 is the same as the representation space of the algebra of square of white noise discovered in Ref. 2. In other words, Boukas' representation extends to a representation of the algebra of square of white noise.

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36

Dornic, Stan, and Tarja Laaksonen. "Continuous Noise, Intermittent Noise, and Annoyance." Perceptual and Motor Skills 68, no. 1 (1989): 11–18. http://dx.doi.org/10.2466/pms.1989.68.1.11.

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In a within-subjects design, 18 subjects listened to white noise, the intensity of which was controlled by themselves. They were instructed to choose the intensity they experienced as “clearly annoying.” Three kinds of white noise were used: continuous, intermittent regular, and intermittent irregular. In the two intermittent conditions, the proportion of time with the noise on was 50%. The duration of on- and off-periods in the regular condition was 1.15 sec.; in the irregular condition, it varied between 0.25 and 1.65 sec. The subjects chose their “clearly annoying” level three times for eac

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37

Singh, D., A. Jain, D. Jain, and V. Goyel. "Effect of white, brown and pink noises on anxious pediatric dental patients." CARDIOMETRY, no. 25 (February 14, 2023): 1252–58. http://dx.doi.org/10.18137/cardiometry.2022.25.12521258.

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Purpose: To evaluate the effectiveness of various relaxation noises on anxiety levels of children aged between 4-8 years old by analysing through heart rate, FLACC scale and Wong-Baker Faces Pain Rating Scale. Material and methodology: Using simple random sampling 40 children were equally divided into group of four; GROUP 1: Control group ( any cartoon music), GROUP 2: White noise, GROUP 3: Brown noise, Group 4: Pink noise. Patients in each group were treated in a single appointment after using the particular sound distraction technique, Patients who all require extraction under local anaesthe

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38

Deon, Aleksei F., Oleg K. Karaduta, and Yulian A. Menyaev. "Phase Congruential White Noise Generator." Algorithms 14, no. 4 (2021): 118. http://dx.doi.org/10.3390/a14040118.

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White noise generators can use uniform random sequences as a basis. However, such a technology may lead to deficient results if the original sequences have insufficient uniformity or omissions of random variables. This article offers a new approach for creating a phase signal generator with an improved matrix of autocorrelation coefficients. As a result, the generated signals of the white noise process have absolutely uniform intensities at the eigen Fourier frequencies. The simulation results confirm that the received signals have an adequate approximation of uniform white noise.

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39

Yokoi, Yoshitaka. "Positive generalized white noise functionals." Hiroshima Mathematical Journal 20, no. 1 (1990): 137–57. http://dx.doi.org/10.32917/hmj/1206454446.

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40

Ji, Un-Cig, and Young-Yi Kim. "CONVOLUTIONS OF WHITE NOISE OPERATORS." Bulletin of the Korean Mathematical Society 48, no. 5 (2011): 1003–14. http://dx.doi.org/10.4134/bkms.2011.48.5.1003.

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41

Ayed, Wided. "Module Free White Noise Flows." Open Systems & Information Dynamics 25, no. 04 (2018): 1850018. http://dx.doi.org/10.1142/s123016121850018x.

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The main result of this paper is to extend to Hilbert module level the proof of the inclusion of (non-Hamiltonian) stochastic differential equations based on free noise into the class of Hamiltonian equations driven by free white noise. To achieve this goal, free white noise calculus is extended to a trivial Hilbert module. The white noise formulation of the Ito table is radically different from the usual Itô tables, both classical and quantum and, combined with the Accardi–Boukas approach to Ito algebra, allows to drastically simplify calculations. Infinitesimal generators of Hilbert module f

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42

Othman, Hakeem A. "The q-Gamma White Noise." Tatra Mountains Mathematical Publications 66, no. 1 (2016): 81–90. http://dx.doi.org/10.1515/tmmp-2016-0022.

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Abstract For 0 < q < 1 and 0 < α < 1, we construct the infinite dimensional q-Gamma white noise measure γα,q by using the Bochner-Minlos theorem. Then we give the chaos decomposition of an L2 space with respect to the measure γα,q via an isomorphism with the 1-mode type interacting Fock space associated to the q-Gamma measure.

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43

KING, NOEL. "Reading White Noise: floating remarks." Critical Quarterly 33, no. 3 (1991): 66–83. http://dx.doi.org/10.1111/j.1467-8705.1991.tb00970.x.

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44

Spencer, J. A., D. J. Moran, A. Lee, and D. Talbert. "White noise and sleep induction." Archives of Disease in Childhood 65, no. 1 (1990): 135–37. http://dx.doi.org/10.1136/adc.65.1.135.

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45

Enchev, Ognian B. "White noise indexed by loops." Annals of Probability 26, no. 3 (1998): 985–99. http://dx.doi.org/10.1214/aop/1022855741.

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46

Ishihara, Masamichi. "Amplification Induced by White Noise." Progress of Theoretical Physics 116, no. 1 (2006): 37–46. http://dx.doi.org/10.1143/ptp.116.37.

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47

Phatak, Sandeep A., Andrew Lovitt, and Jont B. Allen. "Consonant confusions in white noise." Journal of the Acoustical Society of America 124, no. 2 (2008): 1220–33. http://dx.doi.org/10.1121/1.2913251.

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48

Onatski, Alexei, and Harald Uhlig. "UNIT ROOTS IN WHITE NOISE." Econometric Theory 28, no. 3 (2011): 485–508. http://dx.doi.org/10.1017/s0266466611000636.

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Abstract (sommario):

We show that the empirical distribution of the roots of the vector autoregression (VAR) of order p fitted to T observations of a general stationary or nonstationary process converges to the uniform distribution over the unit circle on the complex plane, when both T and p tend to infinity so that (ln T)/p → 0 and p3/T → 0. In particular, even if the process is a white noise, nearly all roots of the estimated VAR will converge by absolute value to unity. For fixed p, we derive an asymptotic approximation to the expected empirical distribution of the estimated roots as T → ∞. The approximation is

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49

Strain, G. M. "White noise: Pigment-associated deafness." Veterinary Journal 188, no. 3 (2011): 247–49. http://dx.doi.org/10.1016/j.tvjl.2010.08.015.

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50

Obata, Nobuaki. "Derivations on white noise functionals." Nagoya Mathematical Journal 139 (September 1995): 21–36. http://dx.doi.org/10.1017/s0027763000005286.

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Abstract (sommario):

The Gaussian space (E*, μ) is a natural infinite dimensional analogue of Euclidean space with Lebesgue measure and a special choice of a Gelfand triple gives a fundamental framework of white noise calculus [2] as distribution theory on Gaussian space. It is proved in Kubo-Takenaka [7] that (E) is a topological algebra under pointwise multiplication. The main purpose of this paper is to answer the fundamental question: what are the derivations on the algebra (E)?

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