S T HESIS - ece umd 2025

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The thesis by Xiaozhong Pang presents a novel neural network design aimed at enhancing approximate dynamic programming (ADP) and optimal multiuser detection. It demonstrates that simultaneous recurrent networks (SRNs) can effectively approximate complex functions, particularly in scenarios where traditional multi-layer perceptrons (MLPs) fail. The research includes empirical tests on three problems: the Net A/Net B problem, maze navigation, and multiuser detection in CDMA systems. Results indicate that SRNs outperform MLPs in function approximation and provide faster solutions to combinatorial optimization challenges, thereby contributing significantly to intelligent control systems.

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