Efficient area and power multiplication part of FFT based on twiddle factor decomposition

2012 ◽  
Author(s):  
Sidinei Ghissoni ◽  
Eduardo Costa ◽  
Jose Monteiro ◽  
Ricardo Reis
Keyword(s):  
Twiddle Factor ◽  
Factor Decomposition

Some comments on inverse arithmetic functions

2004 ◽  
Vol 89 (516) ◽  
pp. 403-408
Author(s):  
P. G. Brown
Keyword(s):  
Number Theory ◽  
Prime Factor ◽  
Arithmetic Functions ◽  
Natural Numbers ◽  
Finite Mathematics ◽  
Factor Decomposition

In many of the basic courses in Number Theory, Finite Mathematics and Cryptography we come across the so-called arithmetic functions such as ϕn), σ(n), τ(n), μ(n), etc, whose domain is the set of natural numbers. These functions are well known and evaluated through the prime factor decomposition of n. It is less well known that these functions possess inverses (with respect to Dirichlet multiplication) which have interesting properties and applications.

Estimation of energy-related carbon emissions in Beijing and factor decomposition analysis

2013 ◽  
Vol 252 ◽  
pp. 258-265 ◽  
Author(s):  
Jinyun Zhang ◽  
Yan Zhang ◽  
Zhifeng Yang ◽  
Brian D. Fath ◽  
Shengsheng Li
Keyword(s):  
Carbon Emissions ◽  
Decomposition Analysis ◽  
Factor Decomposition

Factor decomposition of the Eurozone sovereign CDS spreads

2016 ◽  
Vol 65 ◽  
pp. 1-23 ◽  
Author(s):  
Frank J. Fabozzi ◽  
Rosella Giacometti ◽  
Naoshi Tsuchida
Keyword(s):  
Factor Decomposition

Decomposition analysis of water utilization in the Beijing-Tianjin-Hebei region between 2003 and 2016

2018 ◽  
Vol 19 (2) ◽  
pp. 626-634
Author(s):  
Hongrui Wang ◽  
Siyang Hong ◽  
Tao Cheng ◽  
Xiayue Wang
Keyword(s):  
Socioeconomic Development ◽  
Industrial Structure ◽  
Decomposition Analysis ◽  
Water Shortage ◽  
Structural Effect ◽  
Industrial Water ◽  
Total Water ◽  
Water Utilization ◽  
Internal Relations ◽  
Factor Decomposition

Abstract Water crisis is prominent in the Beijing-Tianjin-Hebei region, therefore, the internal relations between water utilization changes and socioeconomic development must be urgently analysed. Based on analyses of the spatiotemporal characteristics of total water utilization, the factors that influenced changes in industrial water utilization in the Beijing-Tianjin-Hebei region from 2003 to 2016 were studied using a factor decomposition model. The results show that the scaling effect (SCE) increased water utilization by 31.78 billion m3 over those 13 years and was the only driving effect that caused industrial water utilization to increase. The structural effect (STE) and technological effect (TEE) reduced industrial water utilization by 14.93 and 20.44 billion m3, respectively. The TEE was the main reason for the decrease in industrial water utilization in Beijing, accounting for a reduction of 96.5% in total industrial water utilization. The STE was stronger than TEE in Tianjin, with associated decreases of 94.65% and 90.1% in total industrial water utilization, respectively. In Hebei, the STE and TEE reduced total industrial water utilization by 60.23% and 85.46%, respectively. Adjusting the industrial structure and promoting water-saving technology are efficient methods of alleviating the water shortage in the study area.

China's carbon intensity factor decomposition and carbon emission decoupling analysis

Energy ◽  
2021 ◽  
pp. 122175
Author(s):  
Xiongfeng Pan ◽  
Shucen Guo ◽  
Haitao Xu ◽  
Mengyuan Tian ◽  
Xianyou Pan ◽  
...  
Keyword(s):  
Intensity Factor ◽  
Carbon Emission ◽  
Carbon Intensity ◽  
Factor Decomposition ◽  
Decoupling Analysis
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