论文标题
带有光学二次随机草图的信号处理
Signal processing with optical quadratic random sketches
论文作者
论文摘要
随机数据草图（或投影）现在是一种经典技术，例如，具有降低的计算复杂性和内存的近似数值线性代数和机器学习算法。在这种情况下，直接在草图域中直接在未访问原始数据的情况下执行数据处理（例如模式检测或分类）的可能性先前是用于线性随机素描方法和压缩传感的。在这项工作中，我们展示了如何使用光学处理单元实现的随机二次投影直接估算简单的信号处理任务（例如图像中的局部变化）。相同的方法允许直接在草图域中运行的幼稚数据分类方法。我们报告了几项确认我们方法力量的实验。
Random data sketching (or projection) is now a classical technique enabling, for instance, approximate numerical linear algebra and machine learning algorithms with reduced computational complexity and memory. In this context, the possibility of performing data processing (such as pattern detection or classification) directly in the sketched domain without accessing the original data was previously achieved for linear random sketching methods and compressive sensing. In this work, we show how to estimate simple signal processing tasks (such as deducing local variations in a image) directly using random quadratic projections achieved by an optical processing unit. The same approach allows for naive data classification methods directly operated in the sketched domain. We report several experiments confirming the power of our approach.
