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.Analyze the theoretical foundations of information geometry in electrical engineering, focusing on concepts such as Riemannian manifolds, Fisher information, and geometrical structures of probability distributions. How do these theoretical principles provide geometric insights into the structure and geometry of statistical models in machine learning and signal processing?
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