Neural networks are a class of machine learning algorithms inspired by the structure and function of the human brain’s biological neural networks. They consist of interconnected nodes, or neurons, organized in layers, which process information and learn from data through training. These networks excel at pattern recognition and complex data analysis.
Context
The application of neural networks is increasingly prevalent in the analysis of financial markets, including digital assets. News may report on AI-driven trading algorithms, predictive models for price movements, or the use of neural networks in identifying fraudulent transactions. Understanding the capabilities and limitations of neural networks is becoming more important for comprehending sophisticated market analysis tools and emerging technologies in finance.
A groundbreaking digital signature scheme integrates neural networks with multivariate polynomials, establishing robust post-quantum security against adaptive attacks.
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