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Unit 2 discusses learning algorithms, focusing on associative memory, which forms associations between patterns and can be implemented in neural networks. It distinguishes between auto-associative and hetero-associative memories, detailing their functions and applications, including the Hopfield and Bidirectional Associative Memory models. The section also introduces Hebbian learning principles, competitive learning mechanisms, and error correction in artificial neural networks.

Author

rudrachintalwar

Language

EN