Deep learning has proven itself to be a powerful tool to develop datadriven signal processing algorithms for challenging engineering problems. By learning the key features and characteristics of the input signals instead of requiring a human to first identify and model them, learned algorithms can beat many human-made algorithms. In particular, deep neural networks are capable of learning the complicated features of nature-made signals, such as photos and audio recordings, and using them for classification and decision making.

中文翻译：

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深度学习在通信系统物理层的两个应用【讲义】

深度学习已被证明是开发数据驱动信号处理算法以解决具有挑战性的工程问题的强大工具。通过学习输入信号的关键特征和特性，而不是要求人类首先对其进行识别和建模，学习算法可以击败许多人造算法。特别是，深度神经网络能够学习自然信号的复杂特征，例如照片和录音，并将其用于分类和决策。