Results 51 to 60 of about 10,853,875 (318)

Statistical and spectral analysis of wind power: Fractional oscillation dynamics

Physics of Complex Systems, 2021
Time-dependent changes of the wind speed, as for example in Hera Campus (East Timor), are analysed by the statistical and the autocorrelation function in time domain and by the frequency spectrum (frequency domain) using the Fast Fourier Transform (FFT).
Abelito Filipe Belo, Koichi Shimakawa
doaj   +1 more source

Peptide Sequencing With Single Acid Resolution Using a Sub‐Nanometer Diameter Pore

Advanced Functional Materials, EarlyView.
To sequence a single molecule of Aβ1−42–sodium dodecyl sulfate (SDS), the aggregate is forced through a sub‐nanopore 0.4 nm in diameter spanning a 4.0 nm thick membrane. The figure is a visual molecular dynamics (VMD) snapshot depicting the translocation of Aβ1−42–SDS through the pore; only the peptide, the SDS, the Na+ (yellow/green) and Cl− (cyan ...
Apurba Paul, Archith Rayabharam, Lisa Almonte, Eveline Rigo, Joshy Joseph, Ashutosh Kumar, Zhuxin Dong, Narayana Aluru, Gregory Timp   +8 more
wiley   +1 more source

Single-tone frequency estimation based on reformed covariance for half-length autocorrelation

Metrology and Measurement Systems, 2020
This paper presents a new simple and accurate frequency estimator of a sinusoidal signal based on the signal autocorrelation function (ACF). Such an estimator was termed as the reformed covariance for half-length autocorrelation (RC-HLA).
Sergiusz Sienkowski, Mariusz Krajewski
doaj   +1 more source

Subdiffusive behavior in a trapping potential: mean square displacement and velocity autocorrelation function. [PDF]

Physical review. E, Statistical, nonlinear, and soft matter physics, 2009
A theoretical framework for analyzing stochastic data from single-particle tracking in viscoelastic materials and under the influence of a trapping potential is presented. Starting from a generalized Langevin equation, we found analytical expressions for
M. Despósito, A. Viñales
semanticscholar   +1 more source

Fast Autocorrelated Context Models for Data Compression [PDF]

, 2013
A method is presented to automatically generate context models of data by calculating the data's autocorrelation function. The largest values of the autocorrelation function occur at the offsets or lags in the bitstream which tend to be the most highly ...
Scoville, John
core  

Nanomaterial‐Integrated Fiber Neural Probes for Deep Brain Monitoring and Modulation: Challenges and Opportunities

Advanced Functional Materials, EarlyView.
The article presents nanomaterial‐integrated fiber neural probes as innovative tools for deep brain molecular sensing, neural stimulation, and temperature monitoring. It examines breakthroughs in SERS‐based biomolecule detection, thermoplasmonic activation, and luminescent thermometry, alongside strategies to overcome stability, specificity, and ...
Di Zheng, Yang Li, Muhammad Fayyaz Kashif, Linda Piscopo, Massimo De Vittorio, Ferruccio Pisanello   +5 more
wiley   +1 more source

Optimal approximation model of autocorrelation function of digital image

Tongxin xuebao, 2011
Non-stationary stochastic signal was divided into piecewise stationary stochastic signal,and reflecting the sig-nal’s characteristics by autocorrelation function of the piecewise stationary stochastic signal.Generally,the autocorrela-tion function was ...
CHENG Xiao-gang1, CHEN Qi-mei1, CHENG Hao2, LIU Guo-qing2, AN Ming-wei1   +4 more
doaj   +2 more sources

A comprehensive analysis of autocorrelation and bias in home range estimation

Ecological Monographs, 2019
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly ...
M. Noonan, M. Tucker, C. Fleming, T. Akre, S. Alberts, Abdullahi H. Ali, J. Altmann, P. Antunes, J. Belant, D. Beyer, N. Blaum, K. Böhning‐Gaese, L. Cullen, R. C. Paula, J. Dekker, J. Drescher-Lehman, N. Farwig, C. Fichtel, C. Fischer, A. Ford, J. Goheen, R. Janssen, F. Jeltsch, M. Kauffman, P. Kappeler, F. Koch, S. LaPoint, A. Markham, E. P. Medici, R. Morato, R. Nathan, L. Oliveira‐Santos, K. Olson, Bruce D. Patterson, Agustín Paviolo, E. Ramalho, Sascha Rösner, Dana G. Schabo, N. Selva, A. Sergiel, M. Xavier da Silva, O. Spiegel, P. Thompson, W. Ullmann, F. Zięba, T. Zwijacz–Kozica, W. Fagan, T. Mueller, J. Calabrese   +48 more
semanticscholar   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

2-adic complexity of SLCE sequence

Tongxin xuebao, 2019
Aiming at the 2-adic complexity of Sidelnikov-Lempel-Cohn-Eastman sequences,autocorrelation function value of this kind of sequence was obtained by using the cyclotomic number.Based on the relationship between 2-adic complexity and autocorrelation ...
Yan WANG, Shunbo LI, Gaina XUE
doaj   +2 more sources