On Merging Gradient Estimation with Mean-Tracking Techniques for Cluster Identification

1997 ◽  
pp. 63-72 ◽  
Author(s):  
Paul D. Fox ◽  
Elmawati L. Sutanto ◽  
Kevin Warwick
Keyword(s):  
Gradient Estimation ◽  
Cluster Identification

Dimensionality Reduction for Cluster Identification in Metagenomics using Autoencoders

2020 ◽  
Author(s):  
Uditha Maduranga ◽  
Kalana Wijegunarathna ◽  
Sadeep Weerasinghe ◽  
Indika Perera ◽  
Anuradha Wickramarachchi
Keyword(s):  
Dimensionality Reduction ◽  
Cluster Identification

scholarly journals Adaptive Gradient Estimation Stochastic Parallel Gradient Descent Algorithm for Laser Beam Cleanup

Photonics ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 165
Author(s):  
Shiqing Ma ◽  
Ping Yang ◽  
Boheng Lai ◽  
Chunxuan Su ◽  
Wang Zhao ◽  
...  
Keyword(s):  
Solid State ◽  
Adaptive Optics ◽  
Gradient Descent ◽  
Solid State Laser ◽  
Gradient Estimation ◽  
State Laser ◽  
Gradient Descent Algorithm ◽  
Stochastic Parallel Gradient Descent ◽  
High Output ◽  
Improved Algorithm

For a high-power slab solid-state laser, obtaining high output power and high output beam quality are the most important indicators. Adaptive optics systems can significantly improve beam qualities by compensating for the phase distortions of the laser beams. In this paper, we developed an improved algorithm called Adaptive Gradient Estimation Stochastic Parallel Gradient Descent (AGESPGD) algorithm for beam cleanup of a solid-state laser. A second-order gradient of the search point was introduced to modify the gradient estimation, and it was introduced with the adaptive gain coefficient method into the classical Stochastic Parallel Gradient Descent (SPGD) algorithm. The improved algorithm accelerates the search for convergence and prevents it from falling into a local extremum. Simulation and experimental results show that this method reduces the number of iterations by 40%, and the algorithm stability is also improved compared with the original SPGD method.

scholarly journals Small-Scale Coastal Fisheries in the Midst of Adaptation and Diversification: Insights from Southern Italy

2021 ◽  
Vol 13 (13) ◽  
pp. 7393
Author(s):  
Agata Nicolosi ◽  
Donatella Di Gregorio ◽  
Giuseppe Arena ◽  
Valentina Rosa Laganà ◽  
Donatella Privitera
Keyword(s):  
Southern Italy ◽  
Multiple Correspondence Analysis ◽  
Marketing Strategies ◽  
Small Scale ◽  
Artisanal Fishing ◽  
Economic Activities ◽  
Coastal Fisheries ◽  
Cluster Identification ◽  
The Eu

The study looks at the problems facing coastal fishing communities. It highlights the impacts that, in the complex framework of the EU reforms, have manifested themselves on economic activities and on society. The aim of the paper is twofold: to examine small-scale artisanal fishing in an area of Southern Italy in order to develop resilience and diversification and at the same time to outline the profiles of local bluefish buyers to highlight development strategies for the sector. The research carried out through a direct survey by administering a questionnaire to fishermen operating in areas of Southern Italy and the data cross-referenced with the opinions of local consumers. A conjoint experiment, followed by a multiple correspondence analysis and cluster identification, was used to outline the profiles of local bluefish buyers. The results of the analysis reveal that the fish market and the restaurant sector are the main distribution channels preferred by fishermen. Furthermore, fishermen are very sensitive to environmental issues and are willing to collaborate and actively participate in the environmental protection of the sea. Consumers recognise the quality of local bluefish, and they implicitly perceive the sustainability of the method of capture. The results show the need to undertake synergistic actions for the fishing industry, capable of activating marketing strategies adequately to support, promote and develop the sector. The results of the study provide helpful information for food companies in order to better segment their market and target their consumers, as well as to effectively promote their product using brands, certifications and traceability.

Extremum seeking control and gradient estimation based on the Super-Twisting algorithm

2021 ◽  
Vol 105 ◽  
pp. 223-235
Author(s):  
Ixbalank Torres-Zúñiga ◽  
Fernando López-Caamal ◽  
Héctor Hernández-Escoto ◽  
Víctor Alcaraz-González
Keyword(s):  
Extremum Seeking ◽  
Gradient Estimation ◽  
Extremum Seeking Control ◽  
Twisting Algorithm

scholarly journals Gradient estimation for ratios

2002 ◽  
Author(s):  
P.W. Glynn ◽  
P. L'Ecuyer ◽  
M. Ades
Keyword(s):  
Gradient Estimation
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