2022
DOI: 10.1007/s00500-022-07090-z
|View full text |Cite
|
Sign up to set email alerts
|

Key algorithms of digital signal processing based on microwave photonic link and soft computing models

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 25 publications
0
1
0
Order By: Relevance
“…The first section includes 8 research articles on novel soft computing-driven techniques. The discussion includes: analyzing key algorithms of DSP signal processing with soft computing models (Long 2022); proposing a natureinspired optimal feature selection methodology using ant colony optimization for finding the optimal features to reduce the computational complexity and increase detection accuracy (Dharini and Jain 2021); formulating a novel DNN framework for evolving predictive frameworks (Guduru et al 2021); proposing a novel oversampling approach to introduce synthetic samples via genetic algorithm (GA) for evaluating the fault prediction performance and reduced false alarm rate (Arun and Lakshmi 2021); designing and developing a task scheduling method based on a hybrid optimization algorithm to assign a task with minimal amount of waiting time (Khan and Santhosh 2021); proposing a multi-swarm optimization model for multi-cloud scheduling to obtain enhanced quality of services [QoS] in a multi-cloud environment (Mohanraj and Santhosh 2021); by using big data pattern mining algorithm and scene understanding algorithm, a framework optimization system of traditional printing and dyeing process in Xiangxi is developed for the optimization of the traditional model, wherein the edge-driven scene model is applied for the systematic study (Xiao 2021); and studying about soft multimedia assisted new energy productive landscape design based on the environmental analysis and edge-driven artificial intelligence (Ma et al 2021).…”
Section: Editorialmentioning
confidence: 99%
“…The first section includes 8 research articles on novel soft computing-driven techniques. The discussion includes: analyzing key algorithms of DSP signal processing with soft computing models (Long 2022); proposing a natureinspired optimal feature selection methodology using ant colony optimization for finding the optimal features to reduce the computational complexity and increase detection accuracy (Dharini and Jain 2021); formulating a novel DNN framework for evolving predictive frameworks (Guduru et al 2021); proposing a novel oversampling approach to introduce synthetic samples via genetic algorithm (GA) for evaluating the fault prediction performance and reduced false alarm rate (Arun and Lakshmi 2021); designing and developing a task scheduling method based on a hybrid optimization algorithm to assign a task with minimal amount of waiting time (Khan and Santhosh 2021); proposing a multi-swarm optimization model for multi-cloud scheduling to obtain enhanced quality of services [QoS] in a multi-cloud environment (Mohanraj and Santhosh 2021); by using big data pattern mining algorithm and scene understanding algorithm, a framework optimization system of traditional printing and dyeing process in Xiangxi is developed for the optimization of the traditional model, wherein the edge-driven scene model is applied for the systematic study (Xiao 2021); and studying about soft multimedia assisted new energy productive landscape design based on the environmental analysis and edge-driven artificial intelligence (Ma et al 2021).…”
Section: Editorialmentioning
confidence: 99%