Evolution of Systems. Time Scaling and Scaling Factors

1979 ◽  
pp. 289-303
Author(s):  
A. Pacault ◽  
A. Marchand
Keyword(s):  
Scaling Factors ◽  
Time Scaling

Estimation of Scale Factors in Presence of Multiple Signals: Application to sEMG Analysis

2000 ◽  
Vol 39 (02) ◽  
pp. 138-141
Author(s):  
H. Rix ◽  
O. Meste ◽  
W. Muhammad
Keyword(s):  
Maximum Likelihood ◽  
Scaling Factors ◽  
Multiple Signals ◽  
Common Information ◽  
Scale Factors ◽  
Time Scaling ◽  
The Common ◽  
Time Expansion

Abstract:When several realizations of an unknown recurrent signal are observed apart from a time expansion or compression, the classical way of estimating these time scaling factors is to take one signal as reference for the estimation. This approach does not take into account the common information between all possible couples of realizations. To achieve this task we use a Maximum-Likelihood based method, in a sub-optimal manner. Using some realistic assumptions and simplifications, we propose a tractable solution. The improvement of classical results is shown through a simulation whose conclusion is that the larger the number of realizations, the more correct the estimation. Finally, we apply the method to electrically evoked sEMG.

Emergent Project Management: The Time-scaling of Work Routines

2006 ◽  
Author(s):  
Kevin Dooley
Keyword(s):  
Project Management ◽  
Time Scaling ◽  
Work Routines

A SVD and Modified Firefly Optimization Based Robust Digital Image Watermarking Technique

2017 ◽  
Vol 7 (7) ◽  
pp. 268
Author(s):  
Chauhan Usha ◽  
Singh Rajeev Kumar
Keyword(s):  
Digital Media ◽  
Firefly Algorithm ◽  
Image Watermarking ◽  
Singular Values ◽  
Robust Watermarking ◽  
Scaling Factors ◽  
Geometric Attacks ◽  
Host Image ◽  
Firefly Optimization ◽  
Value Decomposition

Digital Watermarking is a technology, to facilitate the authentication, copyright protection and Security of digital media. The objective of developing a robust watermarking technique is to incorporate the maximum possible robustness without compromising with the transparency. Singular Value Decomposition (SVD) using Firefly Algorithm provides this objective of an optimal robust watermarking technique. Multiple scaling factors are used to embed the watermark image into the host by multiplying these scaling factors with the Singular Values (SV) of the host image. Firefly Algorithm is used to optimize the modified host image to achieve the highest possible robustness and transparency. This approach can significantly increase the quality of watermarked image and provide more robustness to the embedded watermark against various attacks such as noise, geometric attacks, filtering attacks etc.

Spectral damping scaling factors for horizontal components of ground motions from subduction earthquakes using NGA-Subduction data

2021 ◽  
pp. 875529302110279
Author(s):  
Sanaz Rezaeian ◽  
Linda Al Atik ◽  
Nicolas M Kuehn ◽  
Norman Abrahamson ◽  
Yousef Bozorgnia ◽  
...  
Keyword(s):  
Ground Motions ◽  
Damping Ratio ◽  
Spectral Shape ◽  
Parametric Models ◽  
Scaling Factors ◽  
Global Models ◽  
Motion Models ◽  
Subduction Earthquakes ◽  
Crustal Earthquakes ◽  
Subduction Zone Earthquakes

This article develops global models of damping scaling factors (DSFs) for subduction zone earthquakes that are functions of the damping ratio, spectral period, earthquake magnitude, and distance. The Next Generation Attenuation for subduction earthquakes (NGA-Sub) project has developed the largest uniformly processed database of recorded ground motions to date from seven subduction regions: Alaska, Cascadia, Central America and Mexico, South America, Japan, Taiwan, and New Zealand. NGA-Sub used this database to develop new ground motion models (GMMs) at a reference 5% damping ratio. We worked with the NGA-Sub project team to develop an extended database that includes pseudo-spectral accelerations (PSA) for 11 damping ratios between 0.5% and 30%. We use this database to develop parametric models of DSF for both interface and intraslab subduction earthquakes that can be used to adjust any subduction GMM from a reference 5% damping ratio to other damping ratios. The DSF is strongly influenced by the response spectral shape and the duration of motion; therefore, in addition to the damping ratio, the median DSF model uses spectral period, magnitude, and distance as surrogate predictor variables to capture the effects of the spectral shape and the duration of motion. We also develop parametric models for the standard deviation of DSF. The models presented in this article are for the RotD50 horizontal component of PSA and are compared with the models for shallow crustal earthquakes in active tectonic regions. Some noticeable differences arise from the considerably longer duration of interface records for very large magnitude events and the enriched high-frequency content of intraslab records, compared with shallow crustal earthquakes. Regional differences are discussed by comparing the proposed global models with the data from each subduction region along with recommendations on the applicability of the models.

scholarly journals Comprehensive Online Network Pruning Via Learnable Scaling Factors

2021 ◽  
Author(s):  
Muhammad Umair Haider ◽  
Murtaza Taj
Keyword(s):  
Scaling Factors ◽  
Network Pruning

scholarly journals Processes controlling the initial mass function: interstellar turbulence and magnetic fields

1991 ◽  
Vol 147 ◽  
pp. 407-408
Author(s):  
R. C. Fleck
Keyword(s):  
Magnetic Fields ◽  
Mass Function ◽  
Diffusion Time ◽  
Interstellar Cloud ◽  
Initial Mass Function ◽  
Mass Scaling ◽  
Interstellar Turbulence ◽  
Time Scaling ◽  
Turbulent Pressure ◽  
Low Mass

The observed flattening of the initial stellar mass function at low mass can be accounted for in terms of the different interstellar cloud size-mass scaling and different ambipolar diffusion time scaling for small, thermally-supported clouds and larger clouds supported primarily by turbulent pressure.

Adaptive laguerre time scaling factor in predictive control

2003 ◽  
Vol 36 (16) ◽  
pp. 1339-1344
Author(s):  
M. El Adel ◽  
M. Ouladsine ◽  
J.C. Carmona
Keyword(s):  
Predictive Control ◽  
Scaling Factor ◽  
Time Scaling

Searching for time-scaling features in rainfall sequences

2007 ◽  
Vol 32 (1) ◽  
pp. 35-41 ◽  
Author(s):  
Luciano Telesca ◽  
Vincenzo Lapenna ◽  
Emanuele Scalcione ◽  
Donato Summa
Keyword(s):  
Time Scaling ◽  
Scaling Features
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