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: Adjustable parameters that are modified during the learning process to minimize error.

Sivanandam et al. provide detailed algorithmic explanations for several foundational learning rules: : Adjustable parameters that are modified during the

A standout feature of this text is its reliance on and the Neural Network Toolbox . Readers are guided through: Readers are guided through: : The book covers

: The book covers various structures, ranging from simple Single-Layer Perceptrons to more complex Multilayer Feedforward Networks and Feedback Networks . Key Learning Rules Covered It establishes that an Artificial Neural Network (ANN)

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The book begins by comparing the human brain's biological neural networks with artificial models. It establishes that an Artificial Neural Network (ANN) is an adaptive system that learns through interconnected nodes (neurons), which are characterized by: