Mathematical Analysis of Neural network -Theory and Computational Network

Neural networks revolutionized artificial intelligence and machine learning because their mathematical basis directly influences their operational efficiency and achievement of desired results. The research examines neural networks through theoretical calculation methods to study mathematical expressions and optimization techniques and stability assessment algorithms. Records of numerical training methods with their respective convergence properties appear in the analysis. Well-designed neural network structures require stringent mathematical models because they produce efficient and resistant network architectures.

Publication Details

Journal
PhilPapers (PhilPapers Foundation)
Published
2025-01-01
Primary Topic
Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
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article

Mathematical Analysis of Neural network -Theory and Computational Network

PhilPapers (PhilPapers Foundation)
Biomedical and Chemical Research
article

Mathematical Analysis of Neural network -Theory and Computational Network

article en

Abstract

Neural networks revolutionized artificial intelligence and machine learning because their mathematical basis directly influences their operational efficiency and achievement of desired results. The research examines neural networks through theoretical calculation methods to study mathematical expressions and optimization techniques and stability assessment algorithms. Records of numerical training methods with their respective convergence properties appear in the analysis. Well-designed neural network structures require stringent mathematical models because they produce efficient and resistant network architectures.

PhilPapers (PhilPapers Foundation)
Openalex Percentile: Top 34%
Biomedical and Chemical Research
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Mathematical Analysis of Neural network -Theory and Computational Network · PhilPapers (PhilPapers Foundation) (2025) | TGRS Research Map | TGRS