Pricing Defaultable Bonds: A New Model Combining Structural Information with the Reduced-Form Approach

2008 ◽  
Author(s):  
Luca Vincenzo Ballestra ◽  
Graziella Pacelli
Keyword(s):  
Structural Information ◽  
Reduced Form ◽  
New Model ◽  
Defaultable Bonds ◽  
Model Combining ◽  
Form Approach

scholarly journals Improved Hough Transform and Total Variation Algorithms for Features Extraction of Wood

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 466
Author(s):  
Weiwei Du ◽  
Yarui Xi ◽  
Kiichi Harada ◽  
Yumei Zhang ◽  
Keiko Nagashima ◽  
...  
Keyword(s):  
Total Variation ◽  
Hough Transform ◽  
Annual Ring ◽  
Wood Quality ◽  
Volume Density ◽  
Low Noise ◽  
Impact Factors ◽  
Annual Rings ◽  
New Model ◽  
Model Combining

Research shows that the intensity impact factors of wood, such as late timber ratio, volume density and the intensity of itself, correlate with the width of wood annual rings. Therefore, extracting wood annual ring information from wood images is helpful for evaluating wood quality. During the past few years, many researchers have conducted defect detection by studying the information of wood images. However, there are few in-depth studies on the statistics and calculation of wood annual ring information. This study proposes a new model combining the Total Variation (TV) algorithm and the improved Hough transform to accurately measure the wood annual ring information. The TV algorithm is used to suppress image noise, and the Hough transform is for detecting the center of the wood image. Moreover, the edges of wood annual rings are extracted, and the statistical ring information is calculated. The experimental results show that the new model has good denoising capability, clearly extract the edges of wood annual rings and calculate the related parameters from the indoor wood images of the processed logs and the unprocessed low-noise logs.

Union Impact: A Reduced Form Approach

1977 ◽  
Vol 59 (4) ◽  
pp. 503 ◽  
Author(s):  
Lawrence M. Kahn
Keyword(s):  
Reduced Form ◽  
Union Impact ◽  
Form Approach

Demystifying the environmental Kuznets curve: turning a black box into a policy tool

1997 ◽  
Vol 2 (4) ◽  
pp. 465-484 ◽  
Author(s):  
THEODORE PANAYOTOU
Keyword(s):  
Economic Growth ◽  
Low Income ◽  
Reduced Form ◽  
Kuznets Curve ◽  
Income Levels ◽  
Policy Tool ◽  
Explicit Consideration ◽  
Speed Up ◽  
Form Approach

The reduced-form approach to the income–environment relationship has been a useful first step towards answering the question of how economic growth affects the environment. However, without an explicit consideration of the underlying determinants of environmental quality, the scope for policy intervention is unduly circumscribed. In this paper a modest attempt is made to incorporate explicit policy considerations into the income–environment relationship and to explore its determinants as a step towards a better understanding of this relationship and its potential as a policy tool. The role of the rate of economic growth and population density is also explored. A main finding is that at least in the case of ambient SO2 levels, policies and institutions can significantly reduce environmental degradation at low income levels and speed up improvements at higher income levels, thereby flattening the EKC and reducing the environmental price of economic growth.

A compensating total variation image denoising model combining L1 and L2 norm

2020 ◽  
pp. 002072092092330
Author(s):  
Liqiong Zhang ◽  
Min Li ◽  
Xiaohua Qiu
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Structural Information ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Isotropic Diffusion ◽  
Model Combining ◽  
L2 Norm ◽  
Staircase Effect

To overcome the “staircase effect” while preserving the structural information such as image edges and textures quickly and effectively, we propose a compensating total variation image denoising model combining L1 and L2 norm. A new compensating regular term is designed, which can perform anisotropic and isotropic diffusion in image denoising, thus making up for insufficient diffusion in the total variation model. The algorithm first uses local standard deviation to distinguish neighborhood types. Then, the anisotropic diffusion based on L1 norm plays the role of edge protection in the strong edge region. The anisotropic and the isotropic diffusion simultaneously exist in the smooth region, so that the weak textures can be protected while overcoming the “staircase effect” effectively. The simulation experiments show that this method can effectively improve the peak signal-to-noise ratio and obtain the higher structural similarity index and the shorter running time.

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